U.S. patent number 11,101,929 [Application Number 16/789,139] was granted by the patent office on 2021-08-24 for dynamically caching data for storage in storage units of a content delivery network.
This patent grant is currently assigned to PURE STORAGE, INC.. The grantee listed for this patent is Pure Storage, Inc.. Invention is credited to Greg Dhuse, S. Christopher Gladwin, Gary W. Grube, Wesley Leggette, Timothy W. Markison, Jason K. Resch, Thomas Franklin Shirley, Jr..
United States Patent |
11,101,929 |
Gladwin , et al. |
August 24, 2021 |
Dynamically caching data for storage in storage units of a content
delivery network
Abstract
A method for execution by a computing device includes,
receiving, from a requesting device, a request for a data segment
of a data object that is or is to be stored in storage units of a
content delivery network. The method further includes determining
whether the data segment is stored in a cache memory of the content
delivery network or in the storage units. When stored in the cache
memory, the method includes retrieving the cached data segment, and
sending it to the requesting device. When stored in the storage
units, the method includes, sending read requests regarding the
data segment to the storage units, receiving, in response to the
read requests, at least a decode threshold number of encoded data
slices, decoding the at least the decode threshold number of
encoded data slices to reproduce the data segment, and sending the
data segment to the requesting device.
Inventors: |
Gladwin; S. Christopher
(Chicago, IL), Markison; Timothy W. (Mesa, AZ), Dhuse;
Greg (Chicago, IL), Shirley, Jr.; Thomas Franklin
(Wauwatosa, WI), Leggette; Wesley (Chicago, IL), Resch;
Jason K. (Chicago, IL), Grube; Gary W. (Barrington
Hills, IL) |
Applicant: |
Name |
City |
State |
Country |
Type |
Pure Storage, Inc. |
Mountain View |
CA |
US |
|
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Assignee: |
PURE STORAGE, INC. (Mountain
View, CA)
|
Family
ID: |
1000004639443 |
Appl.
No.: |
16/789,139 |
Filed: |
February 12, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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16239651 |
Jan 4, 2019 |
10574395 |
|
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15213329 |
Feb 5, 2019 |
10200156 |
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13919566 |
Jan 3, 2017 |
9537609 |
|
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61679000 |
Aug 2, 2012 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
11/2053 (20130101); H03M 13/05 (20130101); H04L
1/0076 (20130101); H04L 67/1097 (20130101); G06F
3/067 (20130101); G06F 11/1076 (20130101); G06F
3/0619 (20130101); G06F 3/064 (20130101); H03M
13/611 (20130101); H04L 69/40 (20130101) |
Current International
Class: |
G06F
15/16 (20060101); G06F 11/10 (20060101); G06F
3/06 (20060101); H04L 1/00 (20060101); G06F
11/20 (20060101); H03M 13/05 (20060101); H04L
29/08 (20060101); H04L 29/14 (20060101); H03M
13/00 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
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Resource Locator; IETF Network Working Group; RFC 4516; Jun. 2006;
pp. 1-15. cited by applicant .
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and Information Science, University of Konstanz; Feb. 2007; 60 pgs.
cited by applicant .
Xin, et al.; Evaluation of Distributed Recovery in Large-Scale
Storage Systems; 13th IEEE International Symposium on High
Performance Distributed Computing; Jun. 2004; pp. 172-181. cited by
applicant .
Zeilenga; Lightweight Directory Access Protocol (LDAP): Technical
Specification Road Map; IETF Network Working Group; RFC 4510; Jun.
2006; pp. 1-8. cited by applicant .
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Information Models; IETF Network Working Group; RFC 4512; Jun.
2006; pp. 1-49. cited by applicant .
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Internationalized String Preparation; IETF Network Working Group;
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Representation of Distinguished Names; IETF Network Working Group;
RFC 4514; Jun. 2006; pp. 1-15. cited by applicant.
|
Primary Examiner: Mundur; Padma
Attorney, Agent or Firm: Garlick & Markison Markison;
Timothy W. Taylor; Timothy D.
Parent Case Text
CROSS REFERENCE TO RELATED PATENTS
The present U.S. Utility Patent application claims priority
pursuant to 35 U.S.C. .sctn. 120 as a continuation of U.S. Utility
application Ser. No. 16/239,651, entitled "STORING A STREAM OF DATA
IN A DISPERSED STORAGE NETWORK", filed Jan. 4, 2019, issuing on
Feb. 25, 2020, which is a continuation of U.S. Utility application
Ser. No. 15/213,329, entitled "STORING A STREAM OF DATA IN A
DISPERSED STORAGE NETWORK", filed Jul. 18, 2016, issued as U.S.
Pat. No. 10,200,156 on Feb. 5, 2019, which is a continuation of
U.S. Utility patent application Ser. No. 13/919,566, entitled
"STORING A STREAM OF DATA IN A DISPERSED STORAGE NETWORK", filed
Jun. 17, 2013, issued as U.S. Pat. No. 9,537,609 on Jan. 3, 2017,
which claims priority pursuant to 35 U.S.C. .sctn. 119(e) to U.S.
Provisional Application No. 61/679,000, entitled "PERFORMANCE
OPTIMIZATION OF A DISTRIBUTED STORAGE AND TASK NETWORK", filed Aug.
2, 2012, all of which are hereby incorporated herein by reference
in their entirety and made part of the present U.S. Utility Patent
Application for all purposes.
Claims
What is claimed is:
1. A method comprises: receiving, from a requesting device of a
storage network, a request for a data segment of a data object that
is or is to be stored in a set of storage units of the storage
network, wherein the data segment, when stored in a cache memory of
the storage network, is stored as the data segment, and when stored
in the set of storage units, is stored as a set of encoded data
slices in accordance with error encoding parameters, wherein at
least a decode threshold number of encoded data slices of the set
of encoded data slices is needed to reproduce the data segment,
wherein the data segment is error encoded to produce the set of
encoded data slices, and wherein a computing device of the storage
network receives the request; determining, by the computing device,
whether the data segment is stored as the data segment in the cache
memory of the storage network or is stored as the set of encoded
data slices in the set of storage units; when the computing device
determines the data segment is stored as the data segment in the
cache memory: retrieving the data segment; and sending the data
segment to the requesting device; and when the computing device
determines the data segment is not stored as the data segment in
the cache memory and the data segment is stored as the set of
encoded data slices in the set of storage units: sending a set of
read requests regarding the set of encoded data slices to the set
of storage units; receiving, in response to the set of read
requests, at least a decode threshold number of encoded data slices
of the set of encoded data slices; decoding the at least the decode
threshold number of encoded data slices in accordance with the
error encoding parameters to reproduce the data segment; and
sending the data segment to the requesting device.
2. The method of claim 1, wherein the error encoding parameters
comprises two or more of: a write threshold number; a read
threshold number; the decode threshold number; a pillar width
number; and a type of error encoding.
3. The method of claim 1 further comprises: subsequent to sending
the data segment to the requesting device, sending the data segment
to the cache memory for temporary storage.
4. The method of claim 1 further comprises: receiving a second data
object for storage in the storage network; and storing the second
data object in the cache memory.
5. The method of claim 4 further comprises: subsequent to storing
the second data object, determining whether the second data object
is substantially the same as a third data object that is stored in
the set of storage units; when the second data object is
substantially the same as the third data object: determining
whether to delete the second data object from the cache memory; and
when determining to delete the second data object, deleting the
second data object form the cache memory.
6. The method of claim 5, wherein the determining to delete the
second data object comprises one or more of: determining a time
period has expired since storing the second data object in the
cache memory; determining an access frequency level is less than an
access frequency threshold; determining available memory of the
cache memory is less than a low memory threshold level; receiving a
delete request to delete the second data object; and determining a
schedule indicated to delete the second data object.
7. The method of claim 5, wherein when the second data object is
not substantially the same as the third data object further
comprises: error encoding the second data object in accordance with
second error encoding parameters to produce a plurality of second
sets of encoded data slices; and sending the plurality of second
sets of encoded data slices to the set of storage units for storage
therein.
8. The method of claim 5, wherein the determining whether the
second data object is substantially the same as the third data
object comprises one or more of: comparing the second data object
to the third data object; comparing a first deterministic value
calculated from the second data object to a second deterministic
value calculated from the third data object; performing a lookup;
and receiving an indication that the second data object is
substantially the same as the third data object.
9. The method of claim 1, wherein the receiving the request further
comprises: receiving, by an internet server, the request for the
data segment; and forwarding, by the internet server, the request
to the computing device.
10. A computer readable memory device comprises: at least one
memory section that stores operational instructions that, when
executed by one or more computing devices of a storage network,
causes the one or more computing devices to: receive, from a
requesting device, a request for a data segment of a data object
that is or is to be stored in a set of storage units of the storage
network, wherein the data segment, when stored in a cache memory of
the storage network, is stored as the data segment, and when stored
in the set of storage units, is stored as a set of encoded data
slices in accordance with error encoding parameters, and wherein
the data segment is error encoded to produce the set of encoded
data slices; determine whether the data segment is stored as the
data segment in a cache of the storage network or is stored as the
set of encoded data slices in the set of storage units; when the
data segment is stored as the data segment in the cache: retrieve
the cached data segment; and send the data segment to the
requesting device; and when the data segment is not stored as the
data segment in the cache and is stored as the set of encoded data
slices in the set of storage units: send a set of read requests
regarding the set of encoded data slices to the set of storage
units; receive, in response to the set of read requests, at least a
decode threshold number of encoded data slices of the set of
encoded data slices; decode the at least the decode threshold
number of encoded data slices in accordance with the error encoding
parameters to reproduce the data segment; and send the data segment
to the requesting device.
11. The computer readable memory device of claim 10, wherein the-at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to determine the error encoding
parameters, and wherein the error encoding parameters include two
or more of: a write threshold number; a read threshold number; the
decode threshold number; a pillar width number; and a type of error
encoding.
12. The computer readable memory device of claim 10, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to: subsequent to sending the data
segment to the requesting device, send the data segment to the
cache memory for temporary storage.
13. The computer readable memory device of claim 10, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to: receive a second data object for
storage in the storage network; and store the second data object in
the cache memory.
14. The computer readable memory device of claim 13, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to: subsequent to storing the second
data object, determine whether the second data object is
substantially the same as a third data object that is stored in the
set of storage units; when the second data object is substantially
the same as the third data object: determine whether to delete the
second data object from the cache memory; and when determining to
delete the second data object, deleting the second data object form
the cache memory.
15. The computer readable memory device of claim 14, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to determine to delete the second
data object by one or more of: determining a time period has
expired since storing the second data object in the cache memory;
determining an access frequency level is less than an access
frequency threshold; determining available memory of the cache
memory is less than a low memory threshold level; receiving a
delete request to delete the second data object; and determining a
schedule indicated to delete the second data object.
16. The computer readable memory device of claim 14, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices, when the second data object is not
substantially the same as the third data object further, to: error
encode the second data object in accordance with second error
encoding parameters to produce a plurality of second sets of
encoded data slices; and send the plurality of second sets of
encoded data slices to the set of storage units for storage
therein.
17. The computer readable memory device of claim 14, wherein the at
least one memory section stores further operational instructions
that, when executed by the one or more computing devices, cause the
one or more computing devices to determine whether the second data
object is substantially the same as the third data object by one or
more of: comparing the second data object to the third data object;
comparing a first deterministic value calculated from the second
data object to a second deterministic value calculated from the
third data object; performing a lookup; and receiving an indication
that the second data object is substantially the same as the third
data object.
Description
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
Not Applicable.
INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT
DISC
Not Applicable.
BACKGROUND OF THE INVENTION
Technical Field of the Invention
This invention relates generally to computer networks and more
particularly to dispersed storage of data and distributed task
processing of data.
Description of Related Art
Computing devices are known to communicate data, process data,
and/or store data. Such computing devices range from wireless smart
phones, laptops, tablets, personal computers (PC), work stations,
and video game devices, to data centers that support millions of
web searches, stock trades, or on-line purchases every day. In
general, a computing device includes a central processing unit
(CPU), a memory system, user input/output interfaces, peripheral
device interfaces, and an interconnecting bus structure.
As is further known, a computer may effectively extend its CPU by
using "cloud computing" to perform one or more computing functions
(e.g., a service, an application, an algorithm, an arithmetic logic
function, etc.) on behalf of the computer. Further, for large
services, applications, and/or functions, cloud computing may be
performed by multiple cloud computing resources in a distributed
manner to improve the response time for completion of the service,
application, and/or function. For example, Hadoop is an open source
software framework that supports distributed applications enabling
application execution by thousands of computers.
In addition to cloud computing, a computer may use "cloud storage"
as part of its memory system. As is known, cloud storage enables a
user, via its computer, to store files, applications, etc. on an
Internet storage system. The Internet storage system may include a
RAID (redundant array of independent disks) system and/or a
dispersed storage system that uses an error correction scheme to
encode data for storage.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
FIG. 1 is a schematic block diagram of an embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 2 is a schematic block diagram of an embodiment of a computing
core in accordance with the present invention;
FIG. 3 is a diagram of an example of a distributed storage and task
processing in accordance with the present invention;
FIG. 4 is a schematic block diagram of an embodiment of an outbound
distributed storage and/or task (DST) processing in accordance with
the present invention;
FIG. 5 is a logic diagram of an example of a method for outbound
DST processing in accordance with the present invention;
FIG. 6 is a schematic block diagram of an embodiment of a dispersed
error encoding in accordance with the present invention;
FIG. 7 is a diagram of an example of a segment processing of the
dispersed error encoding in accordance with the present
invention;
FIG. 8 is a diagram of an example of error encoding and slicing
processing of the dispersed error encoding in accordance with the
present invention;
FIG. 9 is a diagram of an example of grouping selection processing
of the outbound DST processing in accordance with the present
invention;
FIG. 10 is a diagram of an example of converting data into slice
groups in accordance with the present invention;
FIG. 11 is a schematic block diagram of an embodiment of a DST
execution unit in accordance with the present invention;
FIG. 12 is a schematic block diagram of an example of operation of
a DST execution unit in accordance with the present invention;
FIG. 13 is a schematic block diagram of an embodiment of an inbound
distributed storage and/or task (DST) processing in accordance with
the present invention;
FIG. 14 is a logic diagram of an example of a method for inbound
DST processing in accordance with the present invention;
FIG. 15 is a diagram of an example of de-grouping selection
processing of the inbound DST processing in accordance with the
present invention;
FIG. 16 is a schematic block diagram of an embodiment of a
dispersed error decoding in accordance with the present
invention;
FIG. 17 is a diagram of an example of de-slicing and error decoding
processing of the dispersed error decoding in accordance with the
present invention;
FIG. 18 is a diagram of an example of a de-segment processing of
the dispersed error decoding in accordance with the present
invention;
FIG. 19 is a diagram of an example of converting slice groups into
data in accordance with the present invention;
FIG. 20 is a diagram of an example of a distributed storage within
the distributed computing system in accordance with the present
invention;
FIG. 21 is a schematic block diagram of an example of operation of
outbound distributed storage and/or task (DST) processing for
storing data in accordance with the present invention;
FIG. 22 is a schematic block diagram of an example of a dispersed
error encoding for the example of FIG. 21 in accordance with the
present invention;
FIG. 23 is a diagram of an example of converting data into pillar
slice groups for storage in accordance with the present
invention;
FIG. 24 is a schematic block diagram of an example of a storage
operation of a DST execution unit in accordance with the present
invention;
FIG. 25 is a schematic block diagram of an example of operation of
inbound distributed storage and/or task (DST) processing for
retrieving dispersed error encoded data in accordance with the
present invention;
FIG. 26 is a schematic block diagram of an example of a dispersed
error decoding for the example of FIG. 25 in accordance with the
present invention;
FIG. 27 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing a
plurality of data and a plurality of task codes in accordance with
the present invention;
FIG. 28 is a schematic block diagram of an example of the
distributed computing system performing tasks on stored data in
accordance with the present invention;
FIG. 29 is a schematic block diagram of an embodiment of a task
distribution module facilitating the example of FIG. 28 in
accordance with the present invention;
FIG. 30 is a diagram of a specific example of the distributed
computing system performing tasks on stored data in accordance with
the present invention;
FIG. 31 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing data and
task codes for the example of FIG. 30 in accordance with the
present invention;
FIG. 32 is a diagram of an example of DST allocation information
for the example of FIG. 30 in accordance with the present
invention;
FIGS. 33-38 are schematic block diagrams of the DSTN module
performing the example of FIG. 30 in accordance with the present
invention;
FIG. 39 is a diagram of an example of combining result information
into final results for the example of FIG. 30 in accordance with
the present invention;
FIG. 40A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 40B is a schematic block diagram of an embodiment of a
dispersed storage system in accordance with the present
invention;
FIG. 40C is a flowchart illustrating an example of storing data in
accordance with the present invention;
FIG. 41A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 41B is a schematic block diagram of another embodiment of a
dispersed storage system in accordance with the present
invention;
FIG. 41C is a flowchart illustrating another example of storing
data in accordance with the present invention;
FIG. 42 is a flowchart illustrating another example of storing data
in accordance with the present invention;
FIG. 43A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 43B is a flowchart illustrating another example of storing
data in accordance with the present invention;
FIG. 44A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 44B is a diagram illustrating an example of a directory in
accordance with the present invention;
FIG. 44C is a flowchart illustrating another example of storing
data in accordance with the present invention;
FIG. 45A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 45B is a schematic block diagram of an embodiment of a data
interface module in accordance with the present invention;
FIG. 45C is a schematic block diagram of an embodiment of a cache
memory interface in accordance with the present invention;
FIG. 45D is a schematic block diagram of an embodiment of a
distributed storage and task network (DSTN) interface in accordance
with the present invention;
FIG. 45E is a flowchart illustrating an example of encoding data in
accordance with the present invention;
FIG. 45F is a flowchart illustrating an example of decoding
streaming data signals in accordance with the present
invention;
FIG. 45G is a flowchart illustrating another example of storing
data in accordance with the present invention;
FIG. 46A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 46B is a flowchart illustrating another example of storing
data in accordance with the present invention;
FIG. 47A is a schematic block diagram of another embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 47B is a flowchart illustrating another example of storing
data in accordance with the present invention; and
FIG. 48 is a flowchart illustrating another example of storing data
in accordance with the present invention.
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 is a schematic block diagram of an embodiment of a
distributed computing system 10 that includes a user device 12
and/or a user device 14, a distributed storage and/or task (DST)
processing unit 16, a distributed storage and/or task network
(DSTN) managing unit 18, a DST integrity processing unit 20, and a
distributed storage and/or task network (DSTN) module 22. The
components of the distributed computing system 10 are coupled via a
network 24, which may include one or more wireless and/or wire
lined communication systems; one or more private intranet systems
and/or public internet systems; and/or one or more local area
networks (LAN) and/or wide area networks (WAN).
The DSTN module 22 includes a plurality of distributed storage
and/or task (DST) execution units 36 that may be located at
geographically different sites (e.g., one in Chicago, one in
Milwaukee, etc.). Each of the DST execution units is operable to
store dispersed error encoded data and/or to execute, in a
distributed manner, one or more tasks on data. The tasks may be a
simple function (e.g., a mathematical function, a logic function,
an identify function, a find function, a search engine function, a
replace function, etc.), a complex function (e.g., compression,
human and/or computer language translation, text-to-voice
conversion, voice-to-text conversion, etc.), multiple simple and/or
complex functions, one or more algorithms, one or more
applications, etc.
Each of the user devices 12-14, the DST processing unit 16, the
DSTN managing unit 18, and the DST integrity processing unit 20
include a computing core 26, and may be a portable computing device
and/or a fixed computing device. A portable computing device may be
a social networking device, a gaming device, a cell phone, a smart
phone, a personal digital assistant, a digital music player, a
digital video player, a laptop computer, a handheld computer, a
tablet, a video game controller, and/or any other portable device
that includes a computing core. A fixed computing device may be a
personal computer (PC), a computer server, a cable set-top box, a
satellite receiver, a television set, a printer, a fax machine,
home entertainment equipment, a video game console, and/or any type
of home or office computing equipment. User device 12 and DST
processing unit 16 are configured to include a DST client module
34.
With respect to interfaces, each interface 30, 32, and 33 includes
software and/or hardware to support one or more communication links
via the network 24 indirectly and/or directly. For example,
interface 30 supports a communication link (e.g., wired, wireless,
direct, via a LAN, via the network 24, etc.) between user device 14
and the DST processing unit 16. As another example, interface 32
supports communication links (e.g., a wired connection, a wireless
connection, a LAN connection, and/or any other type of connection
to/from the network 24) between user device 12 and the DSTN module
22 and between the DST processing unit 16 and the DSTN module 22.
As yet another example, interface 33 supports a communication link
for each of the DSTN managing unit 18 and DST integrity processing
unit 20 to the network 24.
The distributed computing system 10 is operable to support
dispersed storage (DS) error encoded data storage and retrieval, to
support distributed task processing on received data, and/or to
support distributed task processing on stored data. In general and
with respect to DS error encoded data storage and retrieval, the
distributed computing system 10 supports three primary operations:
storage management, data storage and retrieval (an example of which
will be discussed with reference to FIGS. 20-26), and data storage
integrity verification. In accordance with these three primary
functions, data can be encoded, distributedly stored in physically
different locations, and subsequently retrieved in a reliable and
secure manner. Such a system is tolerant of a significant number of
failures (e.g., up to a failure level, which may be greater than or
equal to a pillar width minus a decode threshold minus one) that
may result from individual storage device failures and/or network
equipment failures without loss of data and without the need for a
redundant or backup copy. Further, the system allows the data to be
stored for an indefinite period of time without data loss and does
so in a secure manner (e.g., the system is very resistant to
attempts at hacking the data).
The second primary function (i.e., distributed data storage and
retrieval) begins and ends with a user device 12-14. For instance,
if a second type of user device 14 has data 40 to store in the DSTN
module 22, it sends the data 40 to the DST processing unit 16 via
its interface 30. The interface 30 functions to mimic a
conventional operating system (OS) file system interface (e.g.,
network file system (NFS), flash file system (FFS), disk file
system (DFS), file transfer protocol (FTP), web-based distributed
authoring and versioning (WebDAV), etc.) and/or a block memory
interface (e.g., small computer system interface (SCSI), internet
small computer system interface (iSCSI), etc.). In addition, the
interface 30 may attach a user identification code (ID) to the data
40.
To support storage management, the DSTN managing unit 18 performs
DS management services. One such DS management service includes the
DSTN managing unit 18 establishing distributed data storage
parameters (e.g., vault creation, distributed storage parameters,
security parameters, billing information, user profile information,
etc.) for a user device 12-14 individually or as part of a group of
user devices. For example, the DSTN managing unit 18 coordinates
creation of a vault (e.g., a virtual memory block) within memory of
the DSTN module 22 for a user device, a group of devices, or for
public access and establishes per vault dispersed storage (DS)
error encoding parameters for a vault. The DSTN managing unit 18
may facilitate storage of DS error encoding parameters for each
vault of a plurality of vaults by updating registry information for
the distributed computing system 10. The facilitating includes
storing updated registry information in one or more of the DSTN
module 22, the user device 12, the DST processing unit 16, and the
DST integrity processing unit 20.
The DS error encoding parameters (e.g., or dispersed storage error
coding parameters) include data segmenting information (e.g., how
many segments data (e.g., a file, a group of files, a data block,
etc.) is divided into), segment security information (e.g., per
segment encryption, compression, integrity checksum, etc.), error
coding information (e.g., pillar width, decode threshold, read
threshold, write threshold, etc.), slicing information (e.g., the
number of encoded data slices that will be created for each data
segment); and slice security information (e.g., per encoded data
slice encryption, compression, integrity checksum, etc.).
The DSTN managing unit 18 creates and stores user profile
information (e.g., an access control list (ACL)) in local memory
and/or within memory of the DSTN module 22. The user profile
information includes authentication information, permissions,
and/or the security parameters. The security parameters may include
encryption/decryption scheme, one or more encryption keys, key
generation scheme, and/or data encoding/decoding scheme.
The DSTN managing unit 18 creates billing information for a
particular user, a user group, a vault access, public vault access,
etc. For instance, the DSTN managing unit 18 tracks the number of
times a user accesses a private vault and/or public vaults, which
can be used to generate a per-access billing information. In
another instance, the DSTN managing unit 18 tracks the amount of
data stored and/or retrieved by a user device and/or a user group,
which can be used to generate a per-data-amount billing
information.
Another DS management service includes the DSTN managing unit 18
performing network operations, network administration, and/or
network maintenance. Network operations includes authenticating
user data allocation requests (e.g., read and/or write requests),
managing creation of vaults, establishing authentication
credentials for user devices, adding/deleting components (e.g.,
user devices, DST execution units, and/or DST processing units)
from the distributed computing system 10, and/or establishing
authentication credentials for DST execution units 36. Network
administration includes monitoring devices and/or units for
failures, maintaining vault information, determining device and/or
unit activation status, determining device and/or unit loading,
and/or determining any other system level operation that affects
the performance level of the system 10. Network maintenance
includes facilitating replacing, upgrading, repairing, and/or
expanding a device and/or unit of the system 10.
To support data storage integrity verification within the
distributed computing system 10, the DST integrity processing unit
20 performs rebuilding of `bad` or missing encoded data slices. At
a high level, the DST integrity processing unit 20 performs
rebuilding by periodically attempting to retrieve/list encoded data
slices, and/or slice names of the encoded data slices, from the
DSTN module 22. For retrieved encoded slices, they are checked for
errors due to data corruption, outdated version, etc. If a slice
includes an error, it is flagged as a `bad` slice. For encoded data
slices that were not received and/or not listed, they are flagged
as missing slices. Bad and/or missing slices are subsequently
rebuilt using other retrieved encoded data slices that are deemed
to be good slices to produce rebuilt slices. The rebuilt slices are
stored in memory of the DSTN module 22. Note that the DST integrity
processing unit 20 may be a separate unit as shown, it may be
included in the DSTN module 22, it may be included in the DST
processing unit 16, and/or distributed among the DST execution
units 36.
To support distributed task processing on received data, the
distributed computing system 10 has two primary operations: DST
(distributed storage and/or task processing) management and DST
execution on received data (an example of which will be discussed
with reference to FIGS. 3-19). With respect to the storage portion
of the DST management, the DSTN managing unit 18 functions as
previously described. With respect to the tasking processing of the
DST management, the DSTN managing unit 18 performs distributed task
processing (DTP) management services. One such DTP management
service includes the DSTN managing unit 18 establishing DTP
parameters (e.g., user-vault affiliation information, billing
information, user-task information, etc.) for a user device 12-14
individually or as part of a group of user devices.
Another DTP management service includes the DSTN managing unit 18
performing DTP network operations, network administration (which is
essentially the same as described above), and/or network
maintenance (which is essentially the same as described above).
Network operations include, but are not limited to, authenticating
user task processing requests (e.g., valid request, valid user,
etc.), authenticating results and/or partial results, establishing
DTP authentication credentials for user devices, adding/deleting
components (e.g., user devices, DST execution units, and/or DST
processing units) from the distributed computing system, and/or
establishing DTP authentication credentials for DST execution
units.
To support distributed task processing on stored data, the
distributed computing system 10 has two primary operations: DST
(distributed storage and/or task) management and DST execution on
stored data. With respect to the DST execution on stored data, if
the second type of user device 14 has a task request 38 for
execution by the DSTN module 22, it sends the task request 38 to
the DST processing unit 16 via its interface 30. An example of DST
execution on stored data will be discussed in greater detail with
reference to FIGS. 27-39. With respect to the DST management, it is
substantially similar to the DST management to support distributed
task processing on received data.
FIG. 2 is a schematic block diagram of an embodiment of a computing
core 26 that includes a processing module 50, a memory controller
52, main memory 54, a video graphics processing unit 55, an
input/output (IO) controller 56, a peripheral component
interconnect (PCI) interface 58, an IO interface module 60, at
least one IO device interface module 62, a read only memory (ROM)
basic input output system (BIOS) 64, and one or more memory
interface modules. The one or more memory interface module(s)
includes one or more of a universal serial bus (USB) interface
module 66, a host bus adapter (HBA) interface module 68, a network
interface module 70, a flash interface module 72, a hard drive
interface module 74, and a DSTN interface module 76.
The DSTN interface module 76 functions to mimic a conventional
operating system (OS) file system interface (e.g., network file
system (NFS), flash file system (FFS), disk file system (DFS), file
transfer protocol (FTP), web-based distributed authoring and
versioning (WebDAV), etc.) and/or a block memory interface (e.g.,
small computer system interface (SCSI), internet small computer
system interface (iSCSI), etc.). The DSTN interface module 76
and/or the network interface module 70 may function as the
interface 30 of the user device 14 of FIG. 1. Further note that the
IO device interface module 62 and/or the memory interface modules
may be collectively or individually referred to as IO ports.
FIG. 3 is a diagram of an example of the distributed computing
system performing a distributed storage and task processing
operation. The distributed computing system includes a DST
(distributed storage and/or task) client module 34 (which may be in
user device 14 and/or in DST processing unit 16 of FIG. 1), a
network 24, a plurality of DST execution units 1-n that includes
two or more DST execution units 36 of FIG. 1 (which form at least a
portion of DSTN module 22 of FIG. 1), a DST managing module (not
shown), and a DST integrity verification module (not shown). The
DST client module 34 includes an outbound DST processing section 80
and an inbound DST processing section 82. Each of the DST execution
units 1-n includes a controller 86, a processing module 84, memory
88, a DT (distributed task) execution module 90, and a DST client
module 34.
In an example of operation, the DST client module 34 receives data
92 and one or more tasks 94 to be performed upon the data 92. The
data 92 may be of any size and of any content, where, due to the
size (e.g., greater than a few Terabytes), the content (e.g.,
secure data, etc.), and/or task(s) (e.g., MIPS intensive),
distributed processing of the task(s) on the data is desired. For
example, the data 92 may be one or more digital books, a copy of a
company's emails, a large-scale Internet search, a video security
file, one or more entertainment video files (e.g., television
programs, movies, etc.), data files, and/or any other large amount
of data (e.g., greater than a few Terabytes).
Within the DST client module 34, the outbound DST processing
section 80 receives the data 92 and the task(s) 94. The outbound
DST processing section 80 processes the data 92 to produce slice
groupings 96. As an example of such processing, the outbound DST
processing section 80 partitions the data 92 into a plurality of
data partitions. For each data partition, the outbound DST
processing section 80 dispersed storage (DS) error encodes the data
partition to produce encoded data slices and groups the encoded
data slices into a slice grouping 96. In addition, the outbound DST
processing section 80 partitions the task 94 into partial tasks 98,
where the number of partial tasks 98 may correspond to the number
of slice groupings 96.
The outbound DST processing section 80 then sends, via the network
24, the slice groupings 96 and the partial tasks 98 to the DST
execution units 1-n of the DSTN module 22 of FIG. 1. For example,
the outbound DST processing section 80 sends slice group 1 and
partial task 1 to DST execution unit 1. As another example, the
outbound DST processing section 80 sends slice group #n and partial
task #n to DST execution unit #n.
Each DST execution unit performs its partial task 98 upon its slice
group 96 to produce partial results 102. For example, DST execution
unit #1 performs partial task #1 on slice group #1 to produce a
partial result #1, for results. As a more specific example, slice
group #1 corresponds to a data partition of a series of digital
books and the partial task #1 corresponds to searching for specific
phrases, recording where the phrase is found, and establishing a
phrase count. In this more specific example, the partial result #1
includes information as to where the phrase was found and includes
the phrase count.
Upon completion of generating their respective partial results 102,
the DST execution units send, via the network 24, their partial
results 102 to the inbound DST processing section 82 of the DST
client module 34. The inbound DST processing section 82 processes
the received partial results 102 to produce a result 104.
Continuing with the specific example of the preceding paragraph,
the inbound DST processing section 82 combines the phrase count
from each of the DST execution units 36 to produce a total phrase
count. In addition, the inbound DST processing section 82 combines
the `where the phrase was found` information from each of the DST
execution units 36 within their respective data partitions to
produce `where the phrase was found` information for the series of
digital books.
In another example of operation, the DST client module 34 requests
retrieval of stored data within the memory of the DST execution
units 36 (e.g., memory of the DSTN module). In this example, the
task 94 is retrieve data stored in the memory of the DSTN module.
Accordingly, the outbound DST processing section 80 converts the
task 94 into a plurality of partial tasks 98 and sends the partial
tasks 98 to the respective DST execution units 1-n.
In response to the partial task 98 of retrieving stored data, a DST
execution unit 36 identifies the corresponding encoded data slices
100 and retrieves them. For example, DST execution unit #1 receives
partial task #1 and retrieves, in response thereto, retrieved
slices #1. The DST execution units 36 send their respective
retrieved slices 100 to the inbound DST processing section 82 via
the network 24.
The inbound DST processing section 82 converts the retrieved slices
100 into data 92. For example, the inbound DST processing section
82 de-groups the retrieved slices 100 to produce encoded slices per
data partition. The inbound DST processing section 82 then DS error
decodes the encoded slices per data partition to produce data
partitions. The inbound DST processing section 82 de-partitions the
data partitions to recapture the data 92.
FIG. 4 is a schematic block diagram of an embodiment of an outbound
distributed storage and/or task (DST) processing section 80 of a
DST client module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1
(e.g., a plurality of n DST execution units 36) via a network 24.
The outbound DST processing section 80 includes a data partitioning
module 110, a dispersed storage (DS) error encoding module 112, a
grouping selector module 114, a control module 116, and a
distributed task control module 118.
In an example of operation, the data partitioning module 110
partitions data 92 into a plurality of data partitions 120. The
number of partitions and the size of the partitions may be selected
by the control module 116 via control 160 based on the data 92
(e.g., its size, its content, etc.), a corresponding task 94 to be
performed (e.g., simple, complex, single step, multiple steps,
etc.), DS encoding parameters (e.g., pillar width, decode
threshold, write threshold, segment security parameters, slice
security parameters, etc.), capabilities of the DST execution units
36 (e.g., processing resources, availability of processing
recourses, etc.), and/or as may be inputted by a user, system
administrator, or other operator (human or automated). For example,
the data partitioning module 110 partitions the data 92 (e.g., 100
Terabytes) into 100,000 data segments, each being 1 Gigabyte in
size. Alternatively, the data partitioning module 110 partitions
the data 92 into a plurality of data segments, where some of data
segments are of a different size, are of the same size, or a
combination thereof.
The DS error encoding module 112 receives the data partitions 120
in a serial manner, a parallel manner, and/or a combination
thereof. For each data partition 120, the DS error encoding module
112 DS error encodes the data partition 120 in accordance with
control information 160 from the control module 116 to produce
encoded data slices 122. The DS error encoding includes segmenting
the data partition into data segments, segment security processing
(e.g., encryption, compression, watermarking, integrity check
(e.g., CRC), etc.), error encoding, slicing, and/or per slice
security processing (e.g., encryption, compression, watermarking,
integrity check (e.g., CRC), etc.). The control information 160
indicates which steps of the DS error encoding are active for a
given data partition and, for active steps, indicates the
parameters for the step. For example, the control information 160
indicates that the error encoding is active and includes error
encoding parameters (e.g., pillar width, decode threshold, write
threshold, read threshold, type of error encoding, etc.).
The grouping selector module 114 groups the encoded slices 122 of a
data partition into a set of slice groupings 96. The number of
slice groupings corresponds to the number of DST execution units 36
identified for a particular task 94. For example, if five DST
execution units 36 are identified for the particular task 94, the
grouping selector module groups the encoded slices 122 of a data
partition into five slice groupings 96. The grouping selector
module 114 outputs the slice groupings 96 to the corresponding DST
execution units 36 via the network 24.
The distributed task control module 118 receives the task 94 and
converts the task 94 into a set of partial tasks 98. For example,
the distributed task control module 118 receives a task to find
where in the data (e.g., a series of books) a phrase occurs and a
total count of the phrase usage in the data. In this example, the
distributed task control module 118 replicates the task 94 for each
DST execution unit 36 to produce the partial tasks 98. In another
example, the distributed task control module 118 receives a task to
find where in the data a first phrase occurs, where in the data a
second phrase occurs, and a total count for each phrase usage in
the data. In this example, the distributed task control module 118
generates a first set of partial tasks 98 for finding and counting
the first phrase and a second set of partial tasks for finding and
counting the second phrase. The distributed task control module 118
sends respective first and/or second partial tasks 98 to each DST
execution unit 36.
FIG. 5 is a logic diagram of an example of a method for outbound
distributed storage and task (DST) processing that begins at step
126 where a DST client module receives data and one or more
corresponding tasks. The method continues at step 128 where the DST
client module determines a number of DST units to support the task
for one or more data partitions. For example, the DST client module
may determine the number of DST units to support the task based on
the size of the data, the requested task, the content of the data,
a predetermined number (e.g., user indicated, system administrator
determined, etc.), available DST units, capability of the DST
units, and/or any other factor regarding distributed task
processing of the data. The DST client module may select the same
DST units for each data partition, may select different DST units
for the data partitions, or a combination thereof.
The method continues at step 130 where the DST client module
determines processing parameters of the data based on the number of
DST units selected for distributed task processing. The processing
parameters include data partitioning information, DS encoding
parameters, and/or slice grouping information. The data
partitioning information includes a number of data partitions, size
of each data partition, and/or organization of the data partitions
(e.g., number of data blocks in a partition, the size of the data
blocks, and arrangement of the data blocks). The DS encoding
parameters include segmenting information, segment security
information, error encoding information (e.g., dispersed storage
error encoding function parameters including one or more of pillar
width, decode threshold, write threshold, read threshold, generator
matrix), slicing information, and/or per slice security
information. The slice grouping information includes information
regarding how to arrange the encoded data slices into groups for
the selected DST units. As a specific example, if the DST client
module determines that five DST units are needed to support the
task, then it determines that the error encoding parameters include
a pillar width of five and a decode threshold of three.
The method continues at step 132 where the DST client module
determines task partitioning information (e.g., how to partition
the tasks) based on the selected DST units and data processing
parameters. The data processing parameters include the processing
parameters and DST unit capability information. The DST unit
capability information includes the number of DT (distributed task)
execution units, execution capabilities of each DT execution unit
(e.g., MIPS capabilities, processing resources (e.g., quantity and
capability of microprocessors, CPUs, digital signal processors,
co-processor, microcontrollers, arithmetic logic circuitry, and/or
any other analog and/or digital processing circuitry), availability
of the processing resources, memory information (e.g., type, size,
availability, etc.)), and/or any information germane to executing
one or more tasks.
The method continues at step 134 where the DST client module
processes the data in accordance with the processing parameters to
produce slice groupings. The method continues at step 136 where the
DST client module partitions the task based on the task
partitioning information to produce a set of partial tasks. The
method continues at step 138 where the DST client module sends the
slice groupings and the corresponding partial tasks to respective
DST units.
FIG. 6 is a schematic block diagram of an embodiment of the
dispersed storage (DS) error encoding module 112 of an outbound
distributed storage and task (DST) processing section. The DS error
encoding module 112 includes a segment processing module 142, a
segment security processing module 144, an error encoding module
146, a slicing module 148, and a per slice security processing
module 150. Each of these modules is coupled to a control module
116 to receive control information 160 therefrom.
In an example of operation, the segment processing module 142
receives a data partition 120 from a data partitioning module and
receives segmenting information as the control information 160 from
the control module 116. The segmenting information indicates how
the segment processing module 142 is to segment the data partition
120. For example, the segmenting information indicates how many
rows to segment the data based on a decode threshold of an error
encoding scheme, indicates how many columns to segment the data
into based on a number and size of data blocks within the data
partition 120, and indicates how many columns to include in a data
segment 152. The segment processing module 142 segments the data
120 into data segments 152 in accordance with the segmenting
information.
The segment security processing module 144, when enabled by the
control module 116, secures the data segments 152 based on segment
security information received as control information 160 from the
control module 116. The segment security information includes data
compression, encryption, watermarking, integrity check (e.g.,
cyclic redundancy check (CRC), etc.), and/or any other type of
digital security. For example, when the segment security processing
module 144 is enabled, it may compress a data segment 152, encrypt
the compressed data segment, and generate a CRC value for the
encrypted data segment to produce a secure data segment 154. When
the segment security processing module 144 is not enabled, it
passes the data segments 152 to the error encoding module 146 or is
bypassed such that the data segments 152 are provided to the error
encoding module 146.
The error encoding module 146 encodes the secure data segments 154
in accordance with error correction encoding parameters received as
control information 160 from the control module 116. The error
correction encoding parameters (e.g., also referred to as dispersed
storage error coding parameters) include identifying an error
correction encoding scheme (e.g., forward error correction
algorithm, a Reed-Solomon based algorithm, an online coding
algorithm, an information dispersal algorithm, etc.), a pillar
width, a decode threshold, a read threshold, a write threshold,
etc. For example, the error correction encoding parameters identify
a specific error correction encoding scheme, specifies a pillar
width of five, and specifies a decode threshold of three. From
these parameters, the error encoding module 146 encodes a data
segment 154 to produce an encoded data segment 156.
The slicing module 148 slices the encoded data segment 156 in
accordance with the pillar width of the error correction encoding
parameters received as control information 160. For example, if the
pillar width is five, the slicing module 148 slices an encoded data
segment 156 into a set of five encoded data slices. As such, for a
plurality of encoded data segments 156 for a given data partition,
the slicing module outputs a plurality of sets of encoded data
slices 158.
The per slice security processing module 150, when enabled by the
control module 116, secures each encoded data slice 158 based on
slice security information received as control information 160 from
the control module 116. The slice security information includes
data compression, encryption, watermarking, integrity check (e.g.,
CRC, etc.), and/or any other type of digital security. For example,
when the per slice security processing module 150 is enabled, it
compresses an encoded data slice 158, encrypts the compressed
encoded data slice, and generates a CRC value for the encrypted
encoded data slice to produce a secure encoded data slice 122. When
the per slice security processing module 150 is not enabled, it
passes the encoded data slices 158 or is bypassed such that the
encoded data slices 158 are the output of the DS error encoding
module 112. Note that the control module 116 may be omitted and
each module stores its own parameters.
FIG. 7 is a diagram of an example of a segment processing of a
dispersed storage (DS) error encoding module. In this example, a
segment processing module 142 receives a data partition 120 that
includes 45 data blocks (e.g., d1-d45), receives segmenting
information (i.e., control information 160) from a control module,
and segments the data partition 120 in accordance with the control
information 160 to produce data segments 152. Each data block may
be of the same size as other data blocks, or of a different size.
In addition, the size of each data block may be a few bytes, to
megabytes of data. As previously mentioned, the segmenting
information indicates how many rows to segment the data partition
into, indicates how many columns to segment the data partition
into, and indicates how many columns to include in a data
segment.
In this example, the decode threshold of the error encoding scheme
is three; as such the number of rows to divide the data partition
into is three. The number of columns for each row is set to 15,
which is based on the number and size of data blocks. The data
blocks of the data partition are arranged in rows and columns in a
sequential order (i.e., the first row includes the first 15 data
blocks; the second row includes the second 15 data blocks; and the
third row includes the last 15 data blocks).
With the data blocks arranged into the desired sequential order,
they are divided into data segments based on the segmenting
information. In this example, the data partition is divided into 8
data segments; the first 7 include 2 columns of three rows and the
last includes 1 column of three rows. Note that the first row of
the 8 data segments is in sequential order of the first 15 data
blocks; the second row of the 8 data segments in sequential order
of the second 15 data blocks; and the third row of the 8 data
segments in sequential order of the last 15 data blocks. Note that
the number of data blocks, the grouping of the data blocks into
segments, and size of the data blocks may vary to accommodate the
desired distributed task processing function.
FIG. 8 is a diagram of an example of error encoding and slicing
processing of the dispersed error encoding processing the data
segments of FIG. 7. In this example, data segment 1 includes 3 rows
with each row being treated as one word for encoding. As such, data
segment 1 includes three words for encoding: word 1 including data
blocks d1 and d2, word 2 including data blocks d16 and d17, and
word 3 including data blocks d31 and d32. Each of data segments 2-7
includes three words where each word includes two data blocks. Data
segment 8 includes three words where each word includes a single
data block (e.g., d15, d30, and d45).
In operation, an error encoding module 146 and a slicing module 148
convert each data segment into a set of encoded data slices in
accordance with error correction encoding parameters as control
information 160. More specifically, when the error correction
encoding parameters indicate a unity matrix Reed-Solomon based
encoding algorithm, 5 pillars, and decode threshold of 3, the first
three encoded data slices of the set of encoded data slices for a
data segment are substantially similar to the corresponding word of
the data segment. For instance, when the unity matrix Reed-Solomon
based encoding algorithm is applied to data segment 1, the content
of the first encoded data slice (DS1_d1&2) of the first set of
encoded data slices (e.g., corresponding to data segment 1) is
substantially similar to content of the first word (e.g., d1 &
d2); the content of the second encoded data slice (DS1_d16&17)
of the first set of encoded data slices is substantially similar to
content of the second word (e.g., d16 & d17); and the content
of the third encoded data slice (DS1_d31&32) of the first set
of encoded data slices is substantially similar to content of the
third word (e.g., d31 & d32).
The content of the fourth and fifth encoded data slices (e.g.,
ES1_1 and ES1_2) of the first set of encoded data slices include
error correction data based on the first-third words of the first
data segment. With such an encoding and slicing scheme, retrieving
any three of the five encoded data slices allows the data segment
to be accurately reconstructed.
The encoding and slicing of data segments 2-7 yield sets of encoded
data slices similar to the set of encoded data slices of data
segment 1. For instance, the content of the first encoded data
slice (DS2_d3&4) of the second set of encoded data slices
(e.g., corresponding to data segment 2) is substantially similar to
content of the first word (e.g., d3 & d4); the content of the
second encoded data slice (DS2_d18&19) of the second set of
encoded data slices is substantially similar to content of the
second word (e.g., d18 & d19); and the content of the third
encoded data slice (DS2_d33&34) of the second set of encoded
data slices is substantially similar to content of the third word
(e.g., d33 & d34). The content of the fourth and fifth encoded
data slices (e.g., ES1_1 and ES1_2) of the second set of encoded
data slices includes error correction data based on the first-third
words of the second data segment.
FIG. 9 is a diagram of an example of grouping selection processing
of an outbound distributed storage and task (DST) processing in
accordance with group selection information as control information
160 from a control module. Encoded slices for data partition 122
are grouped in accordance with the control information 160 to
produce slice groupings 96. In this example, a grouping selector
module 114 organizes the encoded data slices into five slice
groupings (e.g., one for each DST execution unit of a distributed
storage and task network (DSTN) module). As a specific example, the
grouping selector module 114 creates a first slice grouping for a
DST execution unit #1, which includes first encoded slices of each
of the sets of encoded slices. As such, the first DST execution
unit receives encoded data slices corresponding to data blocks 1-15
(e.g., encoded data slices of contiguous data).
The grouping selector module 114 also creates a second slice
grouping for a DST execution unit #2, which includes second encoded
slices of each of the sets of encoded slices. As such, the second
DST execution unit receives encoded data slices corresponding to
data blocks 16-30. The grouping selector module 114 further creates
a third slice grouping for DST execution unit #3, which includes
third encoded slices of each of the sets of encoded slices. As
such, the third DST execution unit receives encoded data slices
corresponding to data blocks 31-45.
The grouping selector module 114 creates a fourth slice grouping
for DST execution unit #4, which includes fourth encoded slices of
each of the sets of encoded slices. As such, the fourth DST
execution unit receives encoded data slices corresponding to first
error encoding information (e.g., encoded data slices of error
coding (EC) data). The grouping selector module 114 further creates
a fifth slice grouping for DST execution unit #5, which includes
fifth encoded slices of each of the sets of encoded slices. As
such, the fifth DST execution unit receives encoded data slices
corresponding to second error encoding information.
FIG. 10 is a diagram of an example of converting data 92 into slice
groups that expands on the preceding figures. As shown, the data 92
is partitioned in accordance with a partitioning function 164 into
a plurality of data partitions (1-x, where x is an integer greater
than 4). Each data partition (or chunkset of data) is encoded and
grouped into slice groupings as previously discussed by an encoding
and grouping function 166. For a given data partition, the slice
groupings are sent to distributed storage and task (DST) execution
units. From data partition to data partition, the ordering of the
slice groupings to the DST execution units may vary.
For example, the slice groupings of data partition #1 is sent to
the DST execution units such that the first DST execution receives
first encoded data slices of each of the sets of encoded data
slices, which corresponds to a first continuous data chunk of the
first data partition (e.g., refer to FIG. 9), a second DST
execution receives second encoded data slices of each of the sets
of encoded data slices, which corresponds to a second continuous
data chunk of the first data partition, etc.
For the second data partition, the slice groupings may be sent to
the DST execution units in a different order than it was done for
the first data partition. For instance, the first slice grouping of
the second data partition (e.g., slice group 2_1) is sent to the
second DST execution unit; the second slice grouping of the second
data partition (e.g., slice group 2_2) is sent to the third DST
execution unit; the third slice grouping of the second data
partition (e.g., slice group 2_3) is sent to the fourth DST
execution unit; the fourth slice grouping of the second data
partition (e.g., slice group 2_4, which includes first error coding
information) is sent to the fifth DST execution unit; and the fifth
slice grouping of the second data partition (e.g., slice group 2_5,
which includes second error coding information) is sent to the
first DST execution unit.
The pattern of sending the slice groupings to the set of DST
execution units may vary in a predicted pattern, a random pattern,
and/or a combination thereof from data partition to data partition.
In addition, from data partition to data partition, the set of DST
execution units may change. For example, for the first data
partition, DST execution units 1-5 may be used; for the second data
partition, DST execution units 6-10 may be used; for the third data
partition, DST execution units 3-7 may be used; etc. As is also
shown, the task is divided into partial tasks that are sent to the
DST execution units in conjunction with the slice groupings of the
data partitions.
FIG. 11 is a schematic block diagram of an embodiment of a DST
(distributed storage and/or task) execution unit that includes an
interface 169, a controller 86, memory 88, one or more DT
(distributed task) execution modules 90, and a DST client module
34. The memory 88 is of sufficient size to store a significant
number of encoded data slices (e.g., thousands of slices to
hundreds-of-millions of slices) and may include one or more hard
drives and/or one or more solid-state memory devices (e.g., flash
memory, DRAM, etc.).
In an example of storing a slice group, the DST execution module
receives a slice grouping 96 (e.g., slice group #1) via interface
169. The slice grouping 96 includes, per partition, encoded data
slices of contiguous data or encoded data slices of error coding
(EC) data. For slice group #1, the DST execution module receives
encoded data slices of contiguous data for partitions #1 and #x
(and potentially others between 3 and x) and receives encoded data
slices of EC data for partitions #2 and #3 (and potentially others
between 3 and x). Examples of encoded data slices of contiguous
data and encoded data slices of error coding (EC) data are
discussed with reference to FIG. 9. The memory 88 stores the
encoded data slices of slice groupings 96 in accordance with memory
control information 174 it receives from the controller 86.
The controller 86 (e.g., a processing module, a CPU, etc.)
generates the memory control information 174 based on a partial
task(s) 98 and distributed computing information (e.g., user
information (e.g., user ID, distributed computing permissions, data
access permission, etc.), vault information (e.g., virtual memory
assigned to user, user group, temporary storage for task
processing, etc.), task validation information, etc.). For example,
the controller 86 interprets the partial task(s) 98 in light of the
distributed computing information to determine whether a requestor
is authorized to perform the task 98, is authorized to access the
data, and/or is authorized to perform the task on this particular
data. When the requestor is authorized, the controller 86
determines, based on the task 98 and/or another input, whether the
encoded data slices of the slice grouping 96 are to be temporarily
stored or permanently stored. Based on the foregoing, the
controller 86 generates the memory control information 174 to write
the encoded data slices of the slice grouping 96 into the memory
88, and to indicate whether the slice grouping 96 is permanently
stored or temporarily stored.
With the slice grouping 96 stored in the memory 88, the controller
86 facilitates execution of the partial task(s) 98. In an example,
the controller 86 interprets the partial task 98 in light of the
capabilities of the DT execution module(s) 90. The capabilities
include one or more of MIPS capabilities, processing resources
(e.g., quantity and capability of microprocessors, CPUs, digital
signal processors, co-processor, microcontrollers, arithmetic logic
circuitry, and/or any other analog and/or digital processing
circuitry), availability of the processing resources, etc. If the
controller 86 determines that the DT execution module(s) 90 have
sufficient capabilities, it generates task control information
176.
The task control information 176 may be a generic instruction
(e.g., perform the task on the stored slice grouping) or a series
of operational codes. In the former instance, the DT execution
module 90 includes a co-processor function specifically configured
(fixed or programmed) to perform the desired task 98. In the latter
instance, the DT execution module 90 includes a general processor
topology where the controller stores an algorithm corresponding to
the particular task 98. In this instance, the controller 86
provides the operational codes (e.g., assembly language, source
code of a programming language, object code, etc.) of the algorithm
to the DT execution module 90 for execution.
Depending on the nature of the task 98, the DT execution module 90
may generate intermediate partial results 102 that are stored in
the memory 88 or in a cache memory (not shown) within the DT
execution module 90. In either case, when the DT execution module
90 completes execution of the partial task 98, it outputs one or
more partial results 102. The partial results 102 may also be
stored in memory 88.
If, when the controller 86 is interpreting whether capabilities of
the DT execution module(s) 90 can support the partial task 98, the
controller 86 determines that the DT execution module(s) 90 cannot
adequately support the task 98 (e.g., does not have the right
resources, does not have sufficient available resources, available
resources would be too slow, etc.), it then determines whether the
partial task 98 should be fully offloaded or partially
offloaded.
If the controller 86 determines that the partial task 98 should be
fully offloaded, it generates DST control information 178 and
provides it to the DST client module 34. The DST control
information 178 includes the partial task 98, memory storage
information regarding the slice grouping 96, and distribution
instructions. The distribution instructions instruct the DST client
module 34 to divide the partial task 98 into sub-partial tasks 172,
to divide the slice grouping 96 into sub-slice groupings 170, and
identify other DST execution units. The DST client module 34
functions in a similar manner as the DST client module 34 of FIGS.
3-10 to produce the sub-partial tasks 172 and the sub-slice
groupings 170 in accordance with the distribution instructions.
The DST client module 34 receives DST feedback 168 (e.g.,
sub-partial results), via the interface 169, from the DST execution
units to which the task was offloaded. The DST client module 34
provides the sub-partial results to the DST execution unit, which
processes the sub-partial results to produce the partial result(s)
102.
If the controller 86 determines that the partial task 98 should be
partially offloaded, it determines what portion of the task 98
and/or slice grouping 96 should be processed locally and what
should be offloaded. For the portion that is being locally
processed, the controller 86 generates task control information 176
as previously discussed. For the portion that is being offloaded,
the controller 86 generates DST control information 178 as
previously discussed.
When the DST client module 34 receives DST feedback 168 (e.g.,
sub-partial results) from the DST executions units to which a
portion of the task was offloaded, it provides the sub-partial
results to the DT execution module 90. The DT execution module 90
processes the sub-partial results with the sub-partial results it
created to produce the partial result(s) 102.
The memory 88 may be further utilized to retrieve one or more of
stored slices 100, stored results 104, partial results 102 when the
DT execution module 90 stores partial results 102 and/or results
104 in the memory 88. For example, when the partial task 98
includes a retrieval request, the controller 86 outputs the memory
control 174 to the memory 88 to facilitate retrieval of slices 100
and/or results 104.
FIG. 12 is a schematic block diagram of an example of operation of
a distributed storage and task (DST) execution unit storing encoded
data slices and executing a task thereon. To store the encoded data
slices of a partition 1 of slice grouping 1, a controller 86
generates write commands as memory control information 174 such
that the encoded slices are stored in desired locations (e.g.,
permanent or temporary) within memory 88.
Once the encoded slices are stored, the controller 86 provides task
control information 176 to a distributed task (DT) execution module
90. As a first step of executing the task in accordance with the
task control information 176, the DT execution module 90 retrieves
the encoded slices from memory 88. The DT execution module 90 then
reconstructs contiguous data blocks of a data partition. As shown
for this example, reconstructed contiguous data blocks of data
partition 1 include data blocks 1-15 (e.g., d1-d15).
With the contiguous data blocks reconstructed, the DT execution
module 90 performs the task on the reconstructed contiguous data
blocks. For example, the task may be to search the reconstructed
contiguous data blocks for a particular word or phrase, identify
where in the reconstructed contiguous data blocks the particular
word or phrase occurred, and/or count the occurrences of the
particular word or phrase on the reconstructed contiguous data
blocks. The DST execution unit continues in a similar manner for
the encoded data slices of other partitions in slice grouping 1.
Note that with using the unity matrix error encoding scheme
previously discussed, if the encoded data slices of contiguous data
are uncorrupted, the decoding of them is a relatively
straightforward process of extracting the data.
If, however, an encoded data slice of contiguous data is corrupted
(or missing), it can be rebuilt by accessing other DST execution
units that are storing the other encoded data slices of the set of
encoded data slices of the corrupted encoded data slice. In this
instance, the DST execution unit having the corrupted encoded data
slices retrieves at least three encoded data slices (of contiguous
data and of error coding data) in the set from the other DST
execution units (recall for this example, the pillar width is 5 and
the decode threshold is 3). The DST execution unit decodes the
retrieved data slices using the DS error encoding parameters to
recapture the corresponding data segment. The DST execution unit
then re-encodes the data segment using the DS error encoding
parameters to rebuild the corrupted encoded data slice. Once the
encoded data slice is rebuilt, the DST execution unit functions as
previously described.
FIG. 13 is a schematic block diagram of an embodiment of an inbound
distributed storage and/or task (DST) processing section 82 of a
DST client module coupled to DST execution units of a distributed
storage and task network (DSTN) module via a network 24. The
inbound DST processing section 82 includes a de-grouping module
180, a DS (dispersed storage) error decoding module 182, a data
de-partitioning module 184, a control module 186, and a distributed
task control module 188. Note that the control module 186 and/or
the distributed task control module 188 may be separate modules
from corresponding ones of outbound DST processing section or may
be the same modules.
In an example of operation, the DST execution units have completed
execution of corresponding partial tasks on the corresponding slice
groupings to produce partial results 102. The inbound DST
processing section 82 receives the partial results 102 via the
distributed task control module 188. The inbound DST processing
section 82 then processes the partial results 102 to produce a
final result, or results 104. For example, if the task was to find
a specific word or phrase within data, the partial results 102
indicate where in each of the prescribed portions of the data the
corresponding DST execution units found the specific word or
phrase. The distributed task control module 188 combines the
individual partial results 102 for the corresponding portions of
the data into a final result 104 for the data as a whole.
In another example of operation, the inbound DST processing section
82 is retrieving stored data from the DST execution units (i.e.,
the DSTN module). In this example, the DST execution units output
encoded data slices 100 corresponding to the data retrieval
requests. The de-grouping module 180 receives retrieved slices 100
and de-groups them to produce encoded data slices per data
partition 122. The DS error decoding module 182 decodes, in
accordance with DS error encoding parameters, the encoded data
slices per data partition 122 to produce data partitions 120.
The data de-partitioning module 184 combines the data partitions
120 into the data 92. The control module 186 controls the
conversion of retrieved slices 100 into the data 92 using control
signals 190 to each of the modules. For instance, the control
module 186 provides de-grouping information to the de-grouping
module 180, provides the DS error encoding parameters to the DS
error decoding module 182, and provides de-partitioning information
to the data de-partitioning module 184.
FIG. 14 is a logic diagram of an example of a method that is
executable by distributed storage and task (DST) client module
regarding inbound DST processing. The method begins at step 194
where the DST client module receives partial results. The method
continues at step 196 where the DST client module retrieves the
task corresponding to the partial results. For example, the partial
results include header information that identifies the requesting
entity, which correlates to the requested task.
The method continues at step 198 where the DST client module
determines result processing information based on the task. For
example, if the task were to identify a particular word or phrase
within the data, the result processing information would indicate
to aggregate the partial results for the corresponding portions of
the data to produce the final result. As another example, if the
task were to count the occurrences of a particular word or phrase
within the data, results of processing the information would
indicate to add the partial results to produce the final results.
The method continues at step 200 where the DST client module
processes the partial results in accordance with the result
processing information to produce the final result or results.
FIG. 15 is a diagram of an example of de-grouping selection
processing of an inbound distributed storage and task (DST)
processing section of a DST client module. In general, this is an
inverse process of the grouping module of the outbound DST
processing section of FIG. 9. Accordingly, for each data partition
(e.g., partition #1), the de-grouping module retrieves the
corresponding slice grouping from the DST execution units (EU)
(e.g., DST 1-5).
As shown, DST execution unit #1 provides a first slice grouping,
which includes the first encoded slices of each of the sets of
encoded slices (e.g., encoded data slices of contiguous data of
data blocks 1-15); DST execution unit #2 provides a second slice
grouping, which includes the second encoded slices of each of the
sets of encoded slices (e.g., encoded data slices of contiguous
data of data blocks 16-30); DST execution unit #3 provides a third
slice grouping, which includes the third encoded slices of each of
the sets of encoded slices (e.g., encoded data slices of contiguous
data of data blocks 31-45); DST execution unit #4 provides a fourth
slice grouping, which includes the fourth encoded slices of each of
the sets of encoded slices (e.g., first encoded data slices of
error coding (EC) data); and DST execution unit #5 provides a fifth
slice grouping, which includes the fifth encoded slices of each of
the sets of encoded slices (e.g., first encoded data slices of
error coding (EC) data).
The de-grouping module de-groups the slice groupings (e.g.,
received slices 100) using a de-grouping selector 180 controlled by
a control signal 190 as shown in the example to produce a plurality
of sets of encoded data slices (e.g., retrieved slices for a
partition into sets of slices 122). Each set corresponding to a
data segment of the data partition.
FIG. 16 is a schematic block diagram of an embodiment of a
dispersed storage (DS) error decoding module 182 of an inbound
distributed storage and task (DST) processing section. The DS error
decoding module 182 includes an inverse per slice security
processing module 202, a de-slicing module 204, an error decoding
module 206, an inverse segment security module 208, a de-segmenting
processing module 210, and a control module 186.
In an example of operation, the inverse per slice security
processing module 202, when enabled by the control module 186,
unsecures each encoded data slice 122 based on slice de-security
information received as control information 190 (e.g., the
compliment of the slice security information discussed with
reference to FIG. 6) received from the control module 186. The
slice security information includes data decompression, decryption,
de-watermarking, integrity check (e.g., CRC verification, etc.),
and/or any other type of digital security. For example, when the
inverse per slice security processing module 202 is enabled, it
verifies integrity information (e.g., a CRC value) of each encoded
data slice 122, it decrypts each verified encoded data slice, and
decompresses each decrypted encoded data slice to produce slice
encoded data 158. When the inverse per slice security processing
module 202 is not enabled, it passes the encoded data slices 122 as
the sliced encoded data 158 or is bypassed such that the retrieved
encoded data slices 122 are provided as the sliced encoded data
158.
The de-slicing module 204 de-slices the sliced encoded data 158
into encoded data segments 156 in accordance with a pillar width of
the error correction encoding parameters received as control
information 190 from the control module 186. For example, if the
pillar width is five, the de-slicing module 204 de-slices a set of
five encoded data slices into an encoded data segment 156. The
error decoding module 206 decodes the encoded data segments 156 in
accordance with error correction decoding parameters received as
control information 190 from the control module 186 to produce
secure data segments 154. The error correction decoding parameters
include identifying an error correction encoding scheme (e.g.,
forward error correction algorithm, a Reed-Solomon based algorithm,
an information dispersal algorithm, etc.), a pillar width, a decode
threshold, a read threshold, a write threshold, etc. For example,
the error correction decoding parameters identify a specific error
correction encoding scheme, specify a pillar width of five, and
specify a decode threshold of three.
The inverse segment security processing module 208, when enabled by
the control module 186, unsecures the secured data segments 154
based on segment security information received as control
information 190 from the control module 186. The segment security
information includes data decompression, decryption,
de-watermarking, integrity check (e.g., CRC, etc.) verification,
and/or any other type of digital security. For example, when the
inverse segment security processing module 208 is enabled, it
verifies integrity information (e.g., a CRC value) of each secure
data segment 154, it decrypts each verified secured data segment,
and decompresses each decrypted secure data segment to produce a
data segment 152. When the inverse segment security processing
module 208 is not enabled, it passes the decoded data segment 154
as the data segment 152 or is bypassed.
The de-segment processing module 210 receives the data segments 152
and receives de-segmenting information as control information 190
from the control module 186. The de-segmenting information
indicates how the de-segment processing module 210 is to de-segment
the data segments 152 into a data partition 120. For example, the
de-segmenting information indicates how the rows and columns of
data segments are to be rearranged to yield the data partition
120.
FIG. 17 is a diagram of an example of de-slicing and error decoding
processing of a dispersed error decoding module. A de-slicing
module 204 receives at least a decode threshold number of encoded
data slices 158 for each data segment in accordance with control
information 190 and provides encoded data 156. In this example, a
decode threshold is three. As such, each set of encoded data slices
158 is shown to have three encoded data slices per data segment.
The de-slicing module 204 may receive three encoded data slices per
data segment because an associated distributed storage and task
(DST) client module requested retrieving only three encoded data
slices per segment or selected three of the retrieved encoded data
slices per data segment. As shown, which is based on the unity
matrix encoding previously discussed with reference to FIG. 8, an
encoded data slice may be a data-based encoded data slice (e.g.,
DS1_d1&d2) or an error code based encoded data slice (e.g.,
ES3_1).
An error decoding module 206 decodes the encoded data 156 of each
data segment in accordance with the error correction decoding
parameters of control information 190 to produce secured segments
154. In this example, data segment 1 includes 3 rows with each row
being treated as one word for encoding. As such, data segment 1
includes three words: word 1 including data blocks d1 and d2, word
2 including data blocks d16 and d17, and word 3 including data
blocks d31 and d32. Each of data segments 2-7 includes three words
where each word includes two data blocks. Data segment 8 includes
three words where each word includes a single data block (e.g.,
d15, d30, and d45).
FIG. 18 is a diagram of an example of a de-segment processing of an
inbound distributed storage and task (DST) processing. In this
example, a de-segment processing module 210 receives data segments
152 (e.g., 1-8) and rearranges the data blocks of the data segments
into rows and columns in accordance with de-segmenting information
of control information 190 to produce a data partition 120. Note
that the number of rows is based on the decode threshold (e.g., 3
in this specific example) and the number of columns is based on the
number and size of the data blocks.
The de-segmenting module 210 converts the rows and columns of data
blocks into the data partition 120. Note that each data block may
be of the same size as other data blocks or of a different size. In
addition, the size of each data block may be a few bytes to
megabytes of data.
FIG. 19 is a diagram of an example of converting slice groups into
data 92 within an inbound distributed storage and task (DST)
processing section. As shown, the data 92 is reconstructed from a
plurality of data partitions (1-x, where x is an integer greater
than 4). Each data partition (or chunk set of data) is decoded and
re-grouped using a de-grouping and decoding function 212 and a
de-partition function 214 from slice groupings as previously
discussed. For a given data partition, the slice groupings (e.g.,
at least a decode threshold per data segment of encoded data
slices) are received from DST execution units. From data partition
to data partition, the ordering of the slice groupings received
from the DST execution units may vary as discussed with reference
to FIG. 10.
FIG. 20 is a diagram of an example of a distributed storage and/or
retrieval within the distributed computing system. The distributed
computing system includes a plurality of distributed storage and/or
task (DST) processing client modules 34 (one shown) coupled to a
distributed storage and/or task processing network (DSTN) module,
or multiple DSTN modules, via a network 24. The DST client module
34 includes an outbound DST processing section 80 and an inbound
DST processing section 82. The DSTN module includes a plurality of
DST execution units. Each DST execution unit includes a controller
86, memory 88, one or more distributed task (DT) execution modules
90, and a DST client module 34.
In an example of data storage, the DST client module 34 has data 92
that it desires to store in the DSTN module. The data 92 may be a
file (e.g., video, audio, text, graphics, etc.), a data object, a
data block, an update to a file, an update to a data block, etc. In
this instance, the outbound DST processing module 80 converts the
data 92 into encoded data slices 216 as will be further described
with reference to FIGS. 21-23. The outbound DST processing module
80 sends, via the network 24, to the DST execution units for
storage as further described with reference to FIG. 24.
In an example of data retrieval, the DST client module 34 issues a
retrieve request to the DST execution units for the desired data
92. The retrieve request may address each DST executions units
storing encoded data slices of the desired data, address a decode
threshold number of DST execution units, address a read threshold
number of DST execution units, or address some other number of DST
execution units. In response to the request, each addressed DST
execution unit retrieves its encoded data slices 100 of the desired
data and sends them to the inbound DST processing section 82, via
the network 24.
When, for each data segment, the inbound DST processing section 82
receives at least a decode threshold number of encoded data slices
100, it converts the encoded data slices 100 into a data segment.
The inbound DST processing section 82 aggregates the data segments
to produce the retrieved data 92.
FIG. 21 is a schematic block diagram of an embodiment of an
outbound distributed storage and/or task (DST) processing section
80 of a DST client module coupled to a distributed storage and task
network (DSTN) module (e.g., a plurality of DST execution units)
via a network 24. The outbound DST processing section 80 includes a
data partitioning module 110, a dispersed storage (DS) error
encoding module 112, a grouping selector module 114, a control
module 116, and a distributed task control module 118.
In an example of operation, the data partitioning module 110 is
by-passed such that data 92 is provided directly to the DS error
encoding module 112. The control module 116 coordinates the
by-passing of the data partitioning module 110 by outputting a
bypass 220 message to the data partitioning module 110.
The DS error encoding module 112 receives the data 92 in a serial
manner, a parallel manner, and/or a combination thereof. The DS
error encoding module 112 DS error encodes the data in accordance
with control information 160 from the control module 116 to produce
encoded data slices 218. The DS error encoding includes segmenting
the data 92 into data segments, segment security processing (e.g.,
encryption, compression, watermarking, integrity check (e.g., CRC,
etc.)), error encoding, slicing, and/or per slice security
processing (e.g., encryption, compression, watermarking, integrity
check (e.g., CRC, etc.)). The control information 160 indicates
which steps of the DS error encoding are active for the data 92
and, for active steps, indicates the parameters for the step. For
example, the control information 160 indicates that the error
encoding is active and includes error encoding parameters (e.g.,
pillar width, decode threshold, write threshold, read threshold,
type of error encoding, etc.).
The grouping selector module 114 groups the encoded slices 218 of
the data segments into pillars of slices 216. The number of pillars
corresponds to the pillar width of the DS error encoding
parameters. In this example, the distributed task control module
118 facilitates the storage request.
FIG. 22 is a schematic block diagram of an example of a dispersed
storage (DS) error encoding module 112 for the example of FIG. 21.
The DS error encoding module 112 includes a segment processing
module 142, a segment security processing module 144, an error
encoding module 146, a slicing module 148, and a per slice security
processing module 150. Each of these modules is coupled to a
control module 116 to receive control information 160
therefrom.
In an example of operation, the segment processing module 142
receives data 92 and receives segmenting information as control
information 160 from the control module 116. The segmenting
information indicates how the segment processing module is to
segment the data. For example, the segmenting information indicates
the size of each data segment. The segment processing module 142
segments the data 92 into data segments 152 in accordance with the
segmenting information.
The segment security processing module 144, when enabled by the
control module 116, secures the data segments 152 based on segment
security information received as control information 160 from the
control module 116. The segment security information includes data
compression, encryption, watermarking, integrity check (e.g., CRC,
etc.), and/or any other type of digital security. For example, when
the segment security processing module 144 is enabled, it
compresses a data segment 152, encrypts the compressed data
segment, and generates a CRC value for the encrypted data segment
to produce a secure data segment. When the segment security
processing module 144 is not enabled, it passes the data segments
152 to the error encoding module 146 or is bypassed such that the
data segments 152 are provided to the error encoding module
146.
The error encoding module 146 encodes the secure data segments in
accordance with error correction encoding parameters received as
control information 160 from the control module 116. The error
correction encoding parameters include identifying an error
correction encoding scheme (e.g., forward error correction
algorithm, a Reed-Solomon based algorithm, an information dispersal
algorithm, etc.), a pillar width, a decode threshold, a read
threshold, a write threshold, etc. For example, the error
correction encoding parameters identify a specific error correction
encoding scheme, specifies a pillar width of five, and specifies a
decode threshold of three. From these parameters, the error
encoding module 146 encodes a data segment to produce an encoded
data segment.
The slicing module 148 slices the encoded data segment in
accordance with a pillar width of the error correction encoding
parameters. For example, if the pillar width is five, the slicing
module slices an encoded data segment into a set of five encoded
data slices. As such, for a plurality of data segments, the slicing
module 148 outputs a plurality of sets of encoded data slices as
shown within encoding and slicing function 222 as described.
The per slice security processing module 150, when enabled by the
control module 116, secures each encoded data slice based on slice
security information received as control information 160 from the
control module 116. The slice security information includes data
compression, encryption, watermarking, integrity check (e.g., CRC,
etc.), and/or any other type of digital security. For example, when
the per slice security processing module 150 is enabled, it may
compress an encoded data slice, encrypt the compressed encoded data
slice, and generate a CRC value for the encrypted encoded data
slice to produce a secure encoded data slice tweaking. When the per
slice security processing module 150 is not enabled, it passes the
encoded data slices or is bypassed such that the encoded data
slices 218 are the output of the DS error encoding module 112.
FIG. 23 is a diagram of an example of converting data 92 into
pillar slice groups utilizing encoding, slicing and pillar grouping
function 224 for storage in memory of a distributed storage and
task network (DSTN) module. As previously discussed, the data 92 is
encoded and sliced into a plurality of sets of encoded data slices;
one set per data segment. The grouping selector module organizes
the sets of encoded data slices into pillars of data slices. In
this example, the DS error encoding parameters include a pillar
width of 5 and a decode threshold of 3. As such, for each data
segment, 5 encoded data slices are created.
The grouping selector module takes the first encoded data slice of
each of the sets and forms a first pillar, which may be sent to the
first DST execution unit. Similarly, the grouping selector module
creates the second pillar from the second slices of the sets; the
third pillar from the third slices of the sets; the fourth pillar
from the fourth slices of the sets; and the fifth pillar from the
fifth slices of the set.
FIG. 24 is a schematic block diagram of an embodiment of a
distributed storage and/or task (DST) execution unit that includes
an interface 169, a controller 86, memory 88, one or more
distributed task (DT) execution modules 90, and a DST client module
34. A computing core 26 may be utilized to implement the one or
more DT execution modules 90 and the DST client module 34. The
memory 88 is of sufficient size to store a significant number of
encoded data slices (e.g., thousands of slices to
hundreds-of-millions of slices) and may include one or more hard
drives and/or one or more solid-state memory devices (e.g., flash
memory, DRAM, etc.).
In an example of storing a pillar of slices 216, the DST execution
unit receives, via interface 169, a pillar of slices 216 (e.g.,
pillar #1 slices). The memory 88 stores the encoded data slices 216
of the pillar of slices in accordance with memory control
information 174 it receives from the controller 86. The controller
86 (e.g., a processing module, a CPU, etc.) generates the memory
control information 174 based on distributed storage information
(e.g., user information (e.g., user ID, distributed storage
permissions, data access permission, etc.), vault information
(e.g., virtual memory assigned to user, user group, etc.), etc.).
Similarly, when retrieving slices, the DST execution unit receives,
via interface 169, a slice retrieval request. The memory 88
retrieves the slice in accordance with memory control information
174 it receives from the controller 86. The memory 88 outputs the
slice 100, via the interface 169, to a requesting entity.
FIG. 25 is a schematic block diagram of an example of operation of
an inbound distributed storage and/or task (DST) processing section
82 for retrieving dispersed error encoded data 92. The inbound DST
processing section 82 includes a de-grouping module 180, a
dispersed storage (DS) error decoding module 182, a data
de-partitioning module 184, a control module 186, and a distributed
task control module 188. Note that the control module 186 and/or
the distributed task control module 188 may be separate modules
from corresponding ones of an outbound DST processing section or
may be the same modules.
In an example of operation, the inbound DST processing section 82
is retrieving stored data 92 from the DST execution units (i.e.,
the DSTN module). In this example, the DST execution units output
encoded data slices corresponding to data retrieval requests from
the distributed task control module 188. The de-grouping module 180
receives pillars of slices 100 and de-groups them in accordance
with control information 190 from the control module 186 to produce
sets of encoded data slices 218. The DS error decoding module 182
decodes, in accordance with the DS error encoding parameters
received as control information 190 from the control module 186,
each set of encoded data slices 218 to produce data segments, which
are aggregated into retrieved data 92. The data de-partitioning
module 184 is by-passed in this operational mode via a bypass
signal 226 of control information 190 from the control module
186.
FIG. 26 is a schematic block diagram of an embodiment of a
dispersed storage (DS) error decoding module 182 of an inbound
distributed storage and task (DST) processing section. The DS error
decoding module 182 includes an inverse per slice security
processing module 202, a de-slicing module 204, an error decoding
module 206, an inverse segment security module 208, and a
de-segmenting processing module 210. The dispersed error decoding
module 182 is operable to de-slice and decode encoded slices per
data segment 218 utilizing a de-slicing and decoding function 228
to produce a plurality of data segments that are de-segmented
utilizing a de-segment function 230 to recover data 92.
In an example of operation, the inverse per slice security
processing module 202, when enabled by the control module 186 via
control information 190, unsecures each encoded data slice 218
based on slice de-security information (e.g., the compliment of the
slice security information discussed with reference to FIG. 6)
received as control information 190 from the control module 186.
The slice de-security information includes data decompression,
decryption, de-watermarking, integrity check (e.g., CRC
verification, etc.), and/or any other type of digital security. For
example, when the inverse per slice security processing module 202
is enabled, it verifies integrity information (e.g., a CRC value)
of each encoded data slice 218, it decrypts each verified encoded
data slice, and decompresses each decrypted encoded data slice to
produce slice encoded data. When the inverse per slice security
processing module 202 is not enabled, it passes the encoded data
slices 218 as the sliced encoded data or is bypassed such that the
retrieved encoded data slices 218 are provided as the sliced
encoded data.
The de-slicing module 204 de-slices the sliced encoded data into
encoded data segments in accordance with a pillar width of the
error correction encoding parameters received as control
information 190 from a control module 186. For example, if the
pillar width is five, the de-slicing module de-slices a set of five
encoded data slices into an encoded data segment. Alternatively,
the encoded data segment may include just three encoded data slices
(e.g., when the decode threshold is 3).
The error decoding module 206 decodes the encoded data segments in
accordance with error correction decoding parameters received as
control information 190 from the control module 186 to produce
secure data segments. The error correction decoding parameters
include identifying an error correction encoding scheme (e.g.,
forward error correction algorithm, a Reed-Solomon based algorithm,
an information dispersal algorithm, etc.), a pillar width, a decode
threshold, a read threshold, a write threshold, etc. For example,
the error correction decoding parameters identify a specific error
correction encoding scheme, specify a pillar width of five, and
specify a decode threshold of three.
The inverse segment security processing module 208, when enabled by
the control module 186, unsecures the secured data segments based
on segment security information received as control information 190
from the control module 186. The segment security information
includes data decompression, decryption, de-watermarking, integrity
check (e.g., CRC, etc.) verification, and/or any other type of
digital security. For example, when the inverse segment security
processing module is enabled, it verifies integrity information
(e.g., a CRC value) of each secure data segment, it decrypts each
verified secured data segment, and decompresses each decrypted
secure data segment to produce a data segment 152. When the inverse
segment security processing module 208 is not enabled, it passes
the decoded data segment 152 as the data segment or is bypassed.
The de-segmenting processing module 210 aggregates the data
segments 152 into the data 92 in accordance with control
information 190 from the control module 186.
FIG. 27 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module that includes a
plurality of distributed storage and task (DST) execution units (#1
through #n, where, for example, n is an integer greater than or
equal to three). Each of the DST execution units includes a DST
client module 34, a controller 86, one or more DT (distributed
task) execution modules 90, and memory 88.
In this example, the DSTN module stores, in the memory of the DST
execution units, a plurality of DS (dispersed storage) encoded data
(e.g., 1 through n, where n is an integer greater than or equal to
two) and stores a plurality of DS encoded task codes (e.g., 1
through k, where k is an integer greater than or equal to two). The
DS encoded data may be encoded in accordance with one or more
examples described with reference to FIGS. 3-19 (e.g., organized in
slice groupings) or encoded in accordance with one or more examples
described with reference to FIGS. 20-26 (e.g., organized in pillar
groups). The data that is encoded into the DS encoded data may be
of any size and/or of any content. For example, the data may be one
or more digital books, a copy of a company's emails, a large-scale
Internet search, a video security file, one or more entertainment
video files (e.g., television programs, movies, etc.), data files,
and/or any other large amount of data (e.g., greater than a few
Terabytes).
The tasks that are encoded into the DS encoded task code may be a
simple function (e.g., a mathematical function, a logic function,
an identify function, a find function, a search engine function, a
replace function, etc.), a complex function (e.g., compression,
human and/or computer language translation, text-to-voice
conversion, voice-to-text conversion, etc.), multiple simple and/or
complex functions, one or more algorithms, one or more
applications, etc. The tasks may be encoded into the DS encoded
task code in accordance with one or more examples described with
reference to FIGS. 3-19 (e.g., organized in slice groupings) or
encoded in accordance with one or more examples described with
reference to FIGS. 20-26 (e.g., organized in pillar groups).
In an example of operation, a DST client module of a user device or
of a DST processing unit issues a DST request to the DSTN module.
The DST request may include a request to retrieve stored data, or a
portion thereof, may include a request to store data that is
included with the DST request, may include a request to perform one
or more tasks on stored data, may include a request to perform one
or more tasks on data included with the DST request, etc. In the
cases where the DST request includes a request to store data or to
retrieve data, the client module and/or the DSTN module processes
the request as previously discussed with reference to one or more
of FIGS. 3-19 (e.g., slice groupings) and/or 20-26 (e.g., pillar
groupings). In the case where the DST request includes a request to
perform one or more tasks on data included with the DST request,
the DST client module and/or the DSTN module process the DST
request as previously discussed with reference to one or more of
FIGS. 3-19.
In the case where the DST request includes a request to perform one
or more tasks on stored data, the DST client module and/or the DSTN
module processes the DST request as will be described with
reference to one or more of FIGS. 28-39. In general, the DST client
module identifies data and one or more tasks for the DSTN module to
execute upon the identified data. The DST request may be for a
one-time execution of the task or for an on-going execution of the
task. As an example of the latter, as a company generates daily
emails, the DST request may be to daily search new emails for
inappropriate content and, if found, record the content, the email
sender(s), the email recipient(s), email routing information,
notify human resources of the identified email, etc.
FIG. 28 is a schematic block diagram of an example of a distributed
computing system performing tasks on stored data. In this example,
two distributed storage and task (DST) client modules 1-2 are
shown: the first may be associated with a user device and the
second may be associated with a DST processing unit or a high
priority user device (e.g., high priority clearance user, system
administrator, etc.). Each DST client module includes a list of
stored data 234 and a list of tasks codes 236. The list of stored
data 234 includes one or more entries of data identifying
information, where each entry identifies data stored in the DSTN
module 22. The data identifying information (e.g., data ID)
includes one or more of a data file name, a data file directory
listing, DSTN addressing information of the data, a data object
identifier, etc. The list of tasks 236 includes one or more entries
of task code identifying information, when each entry identifies
task codes stored in the DSTN module 22. The task code identifying
information (e.g., task ID) includes one or more of a task file
name, a task file directory listing, DSTN addressing information of
the task, another type of identifier to identify the task, etc.
As shown, the list of data 234 and the list of tasks 236 are each
smaller in number of entries for the first DST client module than
the corresponding lists of the second DST client module. This may
occur because the user device associated with the first DST client
module has fewer privileges in the distributed computing system
than the device associated with the second DST client module.
Alternatively, this may occur because the user device associated
with the first DST client module serves fewer users than the device
associated with the second DST client module and is restricted by
the distributed computing system accordingly. As yet another
alternative, this may occur through no restraints by the
distributed computing system, it just occurred because the operator
of the user device associated with the first DST client module has
selected fewer data and/or fewer tasks than the operator of the
device associated with the second DST client module.
In an example of operation, the first DST client module selects one
or more data entries 238 and one or more tasks 240 from its
respective lists (e.g., selected data ID and selected task ID). The
first DST client module sends its selections to a task distribution
module 232. The task distribution module 232 may be within a
stand-alone device of the distributed computing system, may be
within the user device that contains the first DST client module,
or may be within the DSTN module 22.
Regardless of the task distribution module's location, it generates
DST allocation information 242 from the selected task ID 240 and
the selected data ID 238. The DST allocation information 242
includes data partitioning information, task execution information,
and/or intermediate result information. The task distribution
module 232 sends the DST allocation information 242 to the DSTN
module 22. Note that one or more examples of the DST allocation
information will be discussed with reference to one or more of
FIGS. 29-39.
The DSTN module 22 interprets the DST allocation information 242 to
identify the stored DS encoded data (e.g., DS error encoded data 2)
and to identify the stored DS error encoded task code (e.g., DS
error encoded task code 1). In addition, the DSTN module 22
interprets the DST allocation information 242 to determine how the
data is to be partitioned and how the task is to be partitioned.
The DSTN module 22 also determines whether the selected DS error
encoded data 238 needs to be converted from pillar grouping to
slice grouping. If so, the DSTN module 22 converts the selected DS
error encoded data into slice groupings and stores the slice
grouping DS error encoded data by overwriting the pillar grouping
DS error encoded data or by storing it in a different location in
the memory of the DSTN module 22 (i.e., does not overwrite the
pillar grouping DS encoded data).
The DSTN module 22 partitions the data and the task as indicated in
the DST allocation information 242 and sends the portions to
selected DST execution units of the DSTN module 22. Each of the
selected DST execution units performs its partial task(s) on its
slice groupings to produce partial results. The DSTN module 22
collects the partial results from the selected DST execution units
and provides them, as result information 244, to the task
distribution module. The result information 244 may be the
collected partial results, one or more final results as produced by
the DSTN module 22 from processing the partial results in
accordance with the DST allocation information 242, or one or more
intermediate results as produced by the DSTN module 22 from
processing the partial results in accordance with the DST
allocation information 242.
The task distribution module 232 receives the result information
244 and provides one or more final results 104 therefrom to the
first DST client module. The final result(s) 104 may be result
information 244 or a result(s) of the task distribution module's
processing of the result information 244.
In concurrence with processing the selected task of the first DST
client module, the distributed computing system may process the
selected task(s) of the second DST client module on the selected
data(s) of the second DST client module. Alternatively, the
distributed computing system may process the second DST client
module's request subsequent to, or preceding, that of the first DST
client module. Regardless of the ordering and/or parallel
processing of the DST client module requests, the second DST client
module provides its selected data 238 and selected task 240 to a
task distribution module 232. If the task distribution module 232
is a separate device of the distributed computing system or within
the DSTN module, the task distribution modules 232 coupled to the
first and second DST client modules may be the same module. The
task distribution module 232 processes the request of the second
DST client module in a similar manner as it processed the request
of the first DST client module.
FIG. 29 is a schematic block diagram of an embodiment of a task
distribution module 232 facilitating the example of FIG. 28. The
task distribution module 232 includes a plurality of tables it uses
to generate distributed storage and task (DST) allocation
information 242 for selected data and selected tasks received from
a DST client module. The tables include data storage information
248, task storage information 250, distributed task (DT) execution
module information 252, and task .revreaction. sub-task mapping
information 246.
The data storage information table 248 includes a data
identification (ID) field 260, a data size field 262, an addressing
information field 264, distributed storage (DS) information 266,
and may further include other information regarding the data, how
it is stored, and/or how it can be processed. For example, DS
encoded data #1 has a data ID of 1, a data size of AA (e.g., a byte
size of a few Terabytes or more), addressing information of
Addr_1_AA, and DS parameters of 3/5; SEG_1; and SLC_1. In this
example, the addressing information may be a virtual address
corresponding to the virtual address of the first storage word
(e.g., one or more bytes) of the data and information on how to
calculate the other addresses, may be a range of virtual addresses
for the storage words of the data, physical addresses of the first
storage word or the storage words of the data, may be a list of
slice names of the encoded data slices of the data, etc. The DS
parameters may include identity of an error encoding scheme, decode
threshold/pillar width (e.g., 3/5 for the first data entry),
segment security information (e.g., SEG_1), per slice security
information (e.g., SLC_1), and/or any other information regarding
how the data was encoded into data slices.
The task storage information table 250 includes a task
identification (ID) field 268, a task size field 270, an addressing
information field 272, distributed storage (DS) information 274,
and may further include other information regarding the task, how
it is stored, and/or how it can be used to process data. For
example, DS encoded task #2 has a task ID of 2, a task size of XY,
addressing information of Addr_2_XY, and DS parameters of 3/5;
SEG_2; and SLC_2. In this example, the addressing information may
be a virtual address corresponding to the virtual address of the
first storage word (e.g., one or more bytes) of the task and
information on how to calculate the other addresses, may be a range
of virtual addresses for the storage words of the task, physical
addresses of the first storage word or the storage words of the
task, may be a list of slice names of the encoded slices of the
task code, etc. The DS parameters may include identity of an error
encoding scheme, decode threshold/pillar width (e.g., 3/5 for the
first data entry), segment security information (e.g., SEG_2), per
slice security information (e.g., SLC_2), and/or any other
information regarding how the task was encoded into encoded task
slices. Note that the segment and/or the per-slice security
information include a type of encryption (if enabled), a type of
compression (if enabled), watermarking information (if enabled),
and/or an integrity check scheme (if enabled).
The task .revreaction. sub-task mapping information table 246
includes a task field 256 and a sub-task field 258. The task field
256 identifies a task stored in the memory of a distributed storage
and task network (DSTN) module and the corresponding sub-task
fields 258 indicates whether the task includes sub-tasks and, if
so, how many and if any of the sub-tasks are ordered. In this
example, the task .revreaction. sub-task mapping information table
246 includes an entry for each task stored in memory of the DSTN
module (e.g., task 1 through task k). In particular, this example
indicates that task 1 includes 7 sub-tasks; task 2 does not include
sub-tasks, and task k includes r number of sub-tasks (where r is an
integer greater than or equal to two).
The DT execution module table 252 includes a DST execution unit ID
field 276, a DT execution module ID field 278, and a DT execution
module capabilities field 280. The DST execution unit ID field 276
includes the identity of DST units in the DSTN module. The DT
execution module ID field 278 includes the identity of each DT
execution unit in each DST unit. For example, DST unit 1 includes
three DT executions modules (e.g., 1_1, 1_2, and 1_3). The DT
execution capabilities field 280 includes identity of the
capabilities of the corresponding DT execution unit. For example,
DT execution module 1_1 includes capabilities X, where X includes
one or more of MIPS capabilities, processing resources (e.g.,
quantity and capability of microprocessors, CPUs, digital signal
processors, co-processor, microcontrollers, arithmetic logic
circuitry, and/or any other analog and/or digital processing
circuitry), availability of the processing resources, memory
information (e.g., type, size, availability, etc.), and/or any
information germane to executing one or more tasks.
From these tables, the task distribution module 232 generates the
DST allocation information 242 to indicate where the data is
stored, how to partition the data, where the task is stored, how to
partition the task, which DT execution units should perform which
partial task on which data partitions, where and how intermediate
results are to be stored, etc. If multiple tasks are being
performed on the same data or different data, the task distribution
module factors such information into its generation of the DST
allocation information.
FIG. 30 is a diagram of a specific example of a distributed
computing system performing tasks on stored data as a task flow
318. In this example, selected data 92 is data 2 and selected tasks
are tasks 1, 2, and 3. Task 1 corresponds to analyzing translation
of data from one language to another (e.g., human language or
computer language); task 2 corresponds to finding specific words
and/or phrases in the data; and task 3 corresponds to finding
specific translated words and/or phrases in translated data.
In this example, task 1 includes 7 sub-tasks: task 1_1--identify
non-words (non-ordered); task 1_2--identify unique words
(non-ordered); task 1_3--translate (non-ordered); task
1_4--translate back (ordered after task 1_3); task 1_5--compare to
ID errors (ordered after task 1-4); task 1_6--determine non-word
translation errors (ordered after task 1_5 and 1_1); and task
1_7--determine correct translations (ordered after 1_5 and 1_2).
The sub-task further indicates whether they are an ordered task
(i.e., are dependent on the outcome of another task) or non-order
(i.e., are independent of the outcome of another task). Task 2 does
not include sub-tasks and task 3 includes two sub-tasks: task 3_1
translate; and task 3_2 find specific word or phrase in translated
data.
In general, the three tasks collectively are selected to analyze
data for translation accuracies, translation errors, translation
anomalies, occurrence of specific words or phrases in the data, and
occurrence of specific words or phrases on the translated data.
Graphically, the data 92 is translated 306 into translated data
282; is analyzed for specific words and/or phrases 300 to produce a
list of specific words and/or phrases 286; is analyzed for
non-words 302 (e.g., not in a reference dictionary) to produce a
list of non-words 290; and is analyzed for unique words 316
included in the data 92 (i.e., how many different words are
included in the data) to produce a list of unique words 298. Each
of these tasks is independent of each other and can therefore be
processed in parallel if desired.
The translated data 282 is analyzed (e.g., sub-task 3_2) for
specific translated words and/or phrases 304 to produce a list of
specific translated words and/or phrases 288. The translated data
282 is translated back 308 (e.g., sub-task 1_4) into the language
of the original data to produce re-translated data 284. These two
tasks are dependent on the translate task (e.g., task 1_3) and thus
must be ordered after the translation task, which may be in a
pipelined ordering or a serial ordering. The re-translated data 284
is then compared 310 with the original data 92 to find words and/or
phrases that did not translate (one way and/or the other) properly
to produce a list of incorrectly translated words 294. As such, the
comparing task (e.g., sub-task 1_5) 310 is ordered after the
translation 306 and re-translation tasks 308 (e.g., sub-tasks 1_3
and 1_4).
The list of words incorrectly translated 294 is compared 312 to the
list of non-words 290 to identify words that were not properly
translated because the words are non-words to produce a list of
errors due to non-words 292. In addition, the list of words
incorrectly translated 294 is compared 314 to the list of unique
words 298 to identify unique words that were properly translated to
produce a list of correctly translated words 296. The comparison
may also identify unique words that were not properly translated to
produce a list of unique words that were not properly translated.
Note that each list of words (e.g., specific words and/or phrases,
non-words, unique words, translated words and/or phrases, etc.,)
may include the word and/or phrase, how many times it is used,
where in the data it is used, and/or any other information
requested regarding a word and/or phrase.
FIG. 31 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing data and
task codes for the example of FIG. 30. As shown, DS encoded data 2
is stored as encoded data slices across the memory (e.g., stored in
memories 88) of DST execution units 1-5; the DS encoded task code 1
(of task 1) and DS encoded task 3 are stored as encoded task slices
across the memory of DST execution units 1-5; and DS encoded task
code 2 (of task 2) is stored as encoded task slices across the
memory of DST execution units 3-7. As indicated in the data storage
information table and the task storage information table of FIG.
29, the respective data/task has DS parameters of 3/5 for their
decode threshold/pillar width; hence spanning the memory of five
DST execution units.
FIG. 32 is a diagram of an example of distributed storage and task
(DST) allocation information 242 for the example of FIG. 30. The
DST allocation information 242 includes data partitioning
information 320, task execution information 322, and intermediate
result information 324. The data partitioning information 320
includes the data identifier (ID), the number of partitions to
split the data into, address information for each data partition,
and whether the DS encoded data has to be transformed from pillar
grouping to slice grouping. The task execution information 322
includes tabular information having a task identification field
326, a task ordering field 328, a data partition field ID 330, and
a set of DT execution modules 332 to use for the distributed task
processing per data partition. The intermediate result information
324 includes tabular information having a name ID field 334, an ID
of the DST execution unit assigned to process the corresponding
intermediate result 336, a scratch pad storage field 338, and an
intermediate result storage field 340.
Continuing with the example of FIG. 30, where tasks 1-3 are to be
distributedly performed on data 2, the data partitioning
information includes the ID of data 2. In addition, the task
distribution module determines whether the DS encoded data 2 is in
the proper format for distributed computing (e.g., was stored as
slice groupings). If not, the task distribution module indicates
that the DS encoded data 2 format needs to be changed from the
pillar grouping format to the slice grouping format, which will be
done by the DSTN module. In addition, the task distribution module
determines the number of partitions to divide the data into (e.g.,
2_1 through 2_z) and addressing information for each partition.
The task distribution module generates an entry in the task
execution information section for each sub-task to be performed.
For example, task 1_1 (e.g., identify non-words on the data) has no
task ordering (i.e., is independent of the results of other
sub-tasks), is to be performed on data partitions 2_1 through 2_z
by DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1. For instance,
DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 search for
non-words in data partitions 2_1 through 2_z to produce task 1_1
intermediate results (R1-1, which is a list of non-words). Task 1_2
(e.g., identify unique words) has similar task execution
information as task 1_1 to produce task 1_2 intermediate results
(R1-2, which is the list of unique words).
Task 1_3 (e.g., translate) includes task execution information as
being non-ordered (i.e., is independent), having DT execution
modules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1
through 2_4 and having DT execution modules 1_2, 2_2, 3_2, 4_2, and
5_2 translate data partitions 2_5 through 2_z to produce task 1_3
intermediate results (R1-3, which is the translated data). In this
example, the data partitions are grouped, where different sets of
DT execution modules perform a distributed sub-task (or task) on
each data partition group, which allows for further parallel
processing.
Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to
be executed on task 1_3's intermediate result (e.g., R1-3_1) (e.g.,
the translated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and
5_1 are allocated to translate back task 1_3 intermediate result
partitions R1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2,
6_1, 7_1, and 7_2 are allocated to translate back task 1_3
intermediate result partitions R1-3_5 through R1-3_z to produce
task 1-4 intermediate results (R1-4, which is the translated back
data).
Task 1_5 (e.g., compare data and translated data to identify
translation errors) is ordered after task 1_4 and is to be executed
on task 1_4's intermediate results (R4-1) and on the data. DT
execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to
compare the data partitions (2_1 through 2_z) with partitions of
task 1-4 intermediate results partitions R1-4_1 through R1-4_z to
produce task 1_5 intermediate results (R1-5, which is the list
words translated incorrectly).
Task 1_6 (e.g., determine non-word translation errors) is ordered
after tasks 1_1 and 1_5 and is to be executed on tasks 1_1's and
1_5's intermediate results (R1-1 and R1-5). DT execution modules
1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to compare the partitions
of task 1_1 intermediate results (R1-1_1 through R1-1_z) with
partitions of task 1-5 intermediate results partitions (R1-5_1
through R1-5_z) to produce task 1_6 intermediate results (R1-6,
which is the list translation errors due to non-words).
Task 1_7 (e.g., determine words correctly translated) is ordered
after tasks 1_2 and 1_5 and is to be executed on tasks 1_2's and
1_5's intermediate results (R1-1 and R1-5). DT execution modules
1_2, 2_2, 3_2, 4_2, and 5_2 are allocated to compare the partitions
of task 1_2 intermediate results (R1-2_1 through R1-2_z) with
partitions of task 1-5 intermediate results partitions (R1-5_1
through R1-5_z) to produce task 1_7 intermediate results (R1-7,
which is the list of correctly translated words).
Task 2 (e.g., find specific words and/or phrases) has no task
ordering (i.e., is independent of the results of other sub-tasks),
is to be performed on data partitions 2_1 through 2_z by DT
execution modules 3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT
execution modules 3_1, 4_1, 5_1, 6_1, and 7_1 search for specific
words and/or phrases in data partitions 2_1 through 2_z to produce
task 2 intermediate results (R2, which is a list of specific words
and/or phrases).
Task 3_2 (e.g., find specific translated words and/or phrases) is
ordered after task 1_3 (e.g., translate) is to be performed on
partitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2,
3_2, 4_2, and 5_2. For instance, DT execution modules 1_2, 2_2,
3_2, 4_2, and 5_2 search for specific translated words and/or
phrases in the partitions of the translated data (R1-3_1 through
R1-3_z) to produce task 3_2 intermediate results (R3-2, which is a
list of specific translated words and/or phrases).
For each task, the intermediate result information indicates which
DST unit is responsible for overseeing execution of the task and,
if needed, processing the partial results generated by the set of
allocated DT execution units. In addition, the intermediate result
information indicates a scratch pad memory for the task and where
the corresponding intermediate results are to be stored. For
example, for intermediate result R1-1 (the intermediate result of
task 1_1), DST unit 1 is responsible for overseeing execution of
the task 1_1 and coordinates storage of the intermediate result as
encoded intermediate result slices stored in memory of DST
execution units 1-5. In general, the scratch pad is for storing
non-DS encoded intermediate results and the intermediate result
storage is for storing DS encoded intermediate results.
FIGS. 33-38 are schematic block diagrams of the distributed storage
and task network (DSTN) module performing the example of FIG. 30.
In FIG. 33, the DSTN module accesses the data 92 and partitions it
into a plurality of partitions 1-z in accordance with distributed
storage and task network (DST) allocation information. For each
data partition, the DSTN identifies a set of its DT (distributed
task) execution modules 90 to perform the task (e.g., identify
non-words (i.e., not in a reference dictionary) within the data
partition) in accordance with the DST allocation information. From
data partition to data partition, the set of DT execution modules
90 may be the same, different, or a combination thereof (e.g., some
data partitions use the same set while other data partitions use
different sets).
For the first data partition, the first set of DT execution modules
(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation
information of FIG. 32) executes task 1_1 to produce a first
partial result 102 of non-words found in the first data partition.
The second set of DT execution modules (e.g., 1_1, 2_1, 3_1, 4_1,
and 5_1 per the DST allocation information of FIG. 32) executes
task 1_1 to produce a second partial result 102 of non-words found
in the second data partition. The sets of DT execution modules (as
per the DST allocation information) perform task 1_1 on the data
partitions until the "z" set of DT execution modules performs task
1_1 on the "zth" data partition to produce a "zth" partial result
102 of non-words found in the "zth" data partition.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results to produce the first intermediate result (R1-1),
which is a list of non-words found in the data. For instance, each
set of DT execution modules 90 stores its respective partial result
in the scratchpad memory of DST execution unit 1 (which is
identified in the DST allocation or may be determined by DST
execution unit 1). A processing module of DST execution 1 is
engaged to aggregate the first through "zth" partial results to
produce the first intermediate result (e.g., R1_1). The processing
module stores the first intermediate result as non-DS error encoded
data in the scratchpad memory or in another section of memory of
DST execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the first intermediate result (e.g.,
the list of non-words). To begin the encoding, the DST client
module determines whether the list of non-words is of a sufficient
size to partition (e.g., greater than a Terabyte). If yes, it
partitions the first intermediate result (R1-1) into a plurality of
partitions (e.g., R1-1_1 through R1-1_m). If the first intermediate
result is not of sufficient size to partition, it is not
partitioned.
For each partition of the first intermediate result, or for the
first intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 1-5).
In FIG. 34, the DSTN module is performing task 1_2 (e.g., find
unique words) on the data 92. To begin, the DSTN module accesses
the data 92 and partitions it into a plurality of partitions 1-z in
accordance with the DST allocation information or it may use the
data partitions of task 1_1 if the partitioning is the same. For
each data partition, the DSTN identifies a set of its DT execution
modules to perform task 1_2 in accordance with the DST allocation
information. From data partition to data partition, the set of DT
execution modules may be the same, different, or a combination
thereof. For the data partitions, the allocated set of DT execution
modules executes task 1_2 to produce a partial results (e.g.,
1.sup.st through "zth") of unique words found in the data
partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results 102 of task 1_2 to produce the second intermediate
result (R1-2), which is a list of unique words found in the data
92. The processing module of DST execution 1 is engaged to
aggregate the first through "zth" partial results of unique words
to produce the second intermediate result. The processing module
stores the second intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the second intermediate result
(e.g., the list of non-words). To begin the encoding, the DST
client module determines whether the list of unique words is of a
sufficient size to partition (e.g., greater than a Terabyte). If
yes, it partitions the second intermediate result (R1-2) into a
plurality of partitions (e.g., R1-2_1 through R1-2_m). If the
second intermediate result is not of sufficient size to partition,
it is not partitioned.
For each partition of the second intermediate result, or for the
second intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-5).
In FIG. 35, the DSTN module is performing task 1_3 (e.g.,
translate) on the data 92. To begin, the DSTN module accesses the
data 92 and partitions it into a plurality of partitions 1-z in
accordance with the DST allocation information or it may use the
data partitions of task 1_1 if the partitioning is the same. For
each data partition, the DSTN identifies a set of its DT execution
modules to perform task 1_3 in accordance with the DST allocation
information (e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1
translate data partitions 2_1 through 2_4 and DT execution modules
1_2, 2_2, 3_2, 4_2, and 5_2 translate data partitions 2_5 through
2_z). For the data partitions, the allocated set of DT execution
modules 90 executes task 1_3 to produce partial results 102 (e.g.,
1.sup.st through "zth") of translated data.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 2 is assigned to process the first through "zth"
partial results of task 1_3 to produce the third intermediate
result (R1-3), which is translated data. The processing module of
DST execution 2 is engaged to aggregate the first through "zth"
partial results of translated data to produce the third
intermediate result. The processing module stores the third
intermediate result as non-DS error encoded data in the scratchpad
memory or in another section of memory of DST execution unit 2.
DST execution unit 2 engages its DST client module to slice
grouping based DS error encode the third intermediate result (e.g.,
translated data). To begin the encoding, the DST client module
partitions the third intermediate result (R1-3) into a plurality of
partitions (e.g., R1-3_1 through R1-3_y). For each partition of the
third intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 2-6 per the DST allocation information).
As is further shown in FIG. 35, the DSTN module is performing task
1_4 (e.g., retranslate) on the translated data of the third
intermediate result. To begin, the DSTN module accesses the
translated data (from the scratchpad memory or from the
intermediate result memory and decodes it) and partitions it into a
plurality of partitions in accordance with the DST allocation
information. For each partition of the third intermediate result,
the DSTN identifies a set of its DT execution modules 90 to perform
task 1_4 in accordance with the DST allocation information (e.g.,
DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to
translate back partitions R1-3_1 through R1-3_4 and DT execution
modules 1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back
partitions R1-3_5 through R1-3_z). For the partitions, the
allocated set of DT execution modules executes task 1_4 to produce
partial results 102 (e.g., 1.sup.st through "zth") of re-translated
data.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 3 is assigned to process the first through "zth"
partial results of task 1_4 to produce the fourth intermediate
result (R1-4), which is retranslated data. The processing module of
DST execution 3 is engaged to aggregate the first through "zth"
partial results of retranslated data to produce the fourth
intermediate result. The processing module stores the fourth
intermediate result as non-DS error encoded data in the scratchpad
memory or in another section of memory of DST execution unit 3.
DST execution unit 3 engages its DST client module to slice
grouping based DS error encode the fourth intermediate result
(e.g., retranslated data). To begin the encoding, the DST client
module partitions the fourth intermediate result (R1-4) into a
plurality of partitions (e.g., R1-4_1 through R1-4_z). For each
partition of the fourth intermediate result, the DST client module
uses the DS error encoding parameters of the data (e.g., DS
parameters of data 2, which includes 3/5 decode threshold/pillar
width ratio) to produce slice groupings. The slice groupings are
stored in the intermediate result memory (e.g., allocated memory in
the memories of DST execution units 3-7 per the DST allocation
information).
In FIG. 36, a distributed storage and task network (DSTN) module is
performing task 1_5 (e.g., compare) on data 92 and retranslated
data of FIG. 35. To begin, the DSTN module accesses the data 92 and
partitions it into a plurality of partitions in accordance with the
DST allocation information or it may use the data partitions of
task 1_1 if the partitioning is the same. The DSTN module also
accesses the retranslated data from the scratchpad memory, or from
the intermediate result memory and decodes it, and partitions it
into a plurality of partitions in accordance with the DST
allocation information. The number of partitions of the
retranslated data corresponds to the number of partitions of the
data.
For each pair of partitions (e.g., data partition 1 and
retranslated data partition 1), the DSTN identifies a set of its DT
execution modules 90 to perform task 1_5 in accordance with the DST
allocation information (e.g., DT execution modules 1_1, 2_1, 3_1,
4_1, and 5_1). For each pair of partitions, the allocated set of DT
execution modules executes task 1_5 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of incorrectly translated
words and/or phrases.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results of task 1_5 to produce the fifth intermediate
result (R1-5), which is the list of incorrectly translated words
and/or phrases. In particular, the processing module of DST
execution 1 is engaged to aggregate the first through "zth" partial
results of the list of incorrectly translated words and/or phrases
to produce the fifth intermediate result. The processing module
stores the fifth intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the fifth intermediate result. To
begin the encoding, the DST client module partitions the fifth
intermediate result (R1-5) into a plurality of partitions (e.g.,
R1-5_1 through R1-5_z). For each partition of the fifth
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 1-5 per the DST allocation information).
As is further shown in FIG. 36, the DSTN module is performing task
1_6 (e.g., translation errors due to non-words) on the list of
incorrectly translated words and/or phrases (e.g., the fifth
intermediate result R1-5) and the list of non-words (e.g., the
first intermediate result R1-1). To begin, the DSTN module accesses
the lists and partitions them into a corresponding number of
partitions.
For each pair of partitions (e.g., partition R1-1_1 and partition
R1-5_1), the DSTN identifies a set of its DT execution modules 90
to perform task 1_6 in accordance with the DST allocation
information (e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and
5_1). For each pair of partitions, the allocated set of DT
execution modules executes task 1_6 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of incorrectly translated
words and/or phrases due to non-words.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 2 is assigned to process the first through "zth"
partial results of task 1_6 to produce the sixth intermediate
result (R1-6), which is the list of incorrectly translated words
and/or phrases due to non-words. In particular, the processing
module of DST execution 2 is engaged to aggregate the first through
"zth" partial results of the list of incorrectly translated words
and/or phrases due to non-words to produce the sixth intermediate
result. The processing module stores the sixth intermediate result
as non-DS error encoded data in the scratchpad memory or in another
section of memory of DST execution unit 2.
DST execution unit 2 engages its DST client module to slice
grouping based DS error encode the sixth intermediate result. To
begin the encoding, the DST client module partitions the sixth
intermediate result (R1-6) into a plurality of partitions (e.g.,
R1-6_1 through R1-6_z). For each partition of the sixth
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 2-6 per the DST allocation information).
As is still further shown in FIG. 36, the DSTN module is performing
task 1_7 (e.g., correctly translated words and/or phrases) on the
list of incorrectly translated words and/or phrases (e.g., the
fifth intermediate result R1-5) and the list of unique words (e.g.,
the second intermediate result R1-2). To begin, the DSTN module
accesses the lists and partitions them into a corresponding number
of partitions.
For each pair of partitions (e.g., partition R1-2_1 and partition
R1-5_1), the DSTN identifies a set of its DT execution modules 90
to perform task 1_7 in accordance with the DST allocation
information (e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and
5_2). For each pair of partitions, the allocated set of DT
execution modules executes task 1_7 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of correctly translated
words and/or phrases.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 3 is assigned to process the first through "zth"
partial results of task 1_7 to produce the seventh intermediate
result (R1-7), which is the list of correctly translated words
and/or phrases. In particular, the processing module of DST
execution 3 is engaged to aggregate the first through "zth" partial
results of the list of correctly translated words and/or phrases to
produce the seventh intermediate result. The processing module
stores the seventh intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 3.
DST execution unit 3 engages its DST client module to slice
grouping based DS error encode the seventh intermediate result. To
begin the encoding, the DST client module partitions the seventh
intermediate result (R1-7) into a plurality of partitions (e.g.,
R1-7_1 through R1-7_z). For each partition of the seventh
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 3-7 per the DST allocation information).
In FIG. 37, the distributed storage and task network (DSTN) module
is performing task 2 (e.g., find specific words and/or phrases) on
the data 92. To begin, the DSTN module accesses the data and
partitions it into a plurality of partitions 1-z in accordance with
the DST allocation information or it may use the data partitions of
task 1_1 if the partitioning is the same. For each data partition,
the DSTN identifies a set of its DT execution modules 90 to perform
task 2 in accordance with the DST allocation information. From data
partition to data partition, the set of DT execution modules may be
the same, different, or a combination thereof. For the data
partitions, the allocated set of DT execution modules executes task
2 to produce partial results 102 (e.g., 1.sup.st through "zth") of
specific words and/or phrases found in the data partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 7 is assigned to process the first through "zth"
partial results of task 2 to produce task 2 intermediate result
(R2), which is a list of specific words and/or phrases found in the
data. The processing module of DST execution 7 is engaged to
aggregate the first through "zth" partial results of specific words
and/or phrases to produce the task 2 intermediate result. The
processing module stores the task 2 intermediate result as non-DS
error encoded data in the scratchpad memory or in another section
of memory of DST execution unit 7.
DST execution unit 7 engages its DST client module to slice
grouping based DS error encode the task 2 intermediate result. To
begin the encoding, the DST client module determines whether the
list of specific words and/or phrases is of a sufficient size to
partition (e.g., greater than a Terabyte). If yes, it partitions
the task 2 intermediate result (R2) into a plurality of partitions
(e.g., R2_1 through R2 m). If the task 2 intermediate result is not
of sufficient size to partition, it is not partitioned.
For each partition of the task 2 intermediate result, or for the
task 2 intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-4, and 7).
In FIG. 38, the distributed storage and task network (DSTN) module
is performing task 3 (e.g., find specific translated words and/or
phrases) on the translated data (R1-3). To begin, the DSTN module
accesses the translated data (from the scratchpad memory or from
the intermediate result memory and decodes it) and partitions it
into a plurality of partitions in accordance with the DST
allocation information. For each partition, the DSTN identifies a
set of its DT execution modules to perform task 3 in accordance
with the DST allocation information. From partition to partition,
the set of DT execution modules may be the same, different, or a
combination thereof. For the partitions, the allocated set of DT
execution modules 90 executes task 3 to produce partial results 102
(e.g., 1.sup.st through "zth") of specific translated words and/or
phrases found in the data partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 5 is assigned to process the first through "zth"
partial results of task 3 to produce task 3 intermediate result
(R3), which is a list of specific translated words and/or phrases
found in the translated data. In particular, the processing module
of DST execution 5 is engaged to aggregate the first through "zth"
partial results of specific translated words and/or phrases to
produce the task 3 intermediate result. The processing module
stores the task 3 intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 7.
DST execution unit 5 engages its DST client module to slice
grouping based DS error encode the task 3 intermediate result. To
begin the encoding, the DST client module determines whether the
list of specific translated words and/or phrases is of a sufficient
size to partition (e.g., greater than a Terabyte). If yes, it
partitions the task 3 intermediate result (R3) into a plurality of
partitions (e.g., R3_1 through R3 m). If the task 3 intermediate
result is not of sufficient size to partition, it is not
partitioned.
For each partition of the task 3 intermediate result, or for the
task 3 intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-4, 5, and 7).
FIG. 39 is a diagram of an example of combining result information
into final results 104 for the example of FIG. 30. In this example,
the result information includes the list of specific words and/or
phrases found in the data (task 2 intermediate result), the list of
specific translated words and/or phrases found in the data (task 3
intermediate result), the list of non-words found in the data (task
1 first intermediate result R1-1), the list of unique words found
in the data (task 1 second intermediate result R1-2), the list of
translation errors due to non-words (task 1 sixth intermediate
result R1-6), and the list of correctly translated words and/or
phrases (task 1 seventh intermediate result R1-7). The task
distribution module provides the result information to the
requesting DST client module as the results 104.
FIG. 40A is a schematic block diagram of another embodiment of a
distributed computing system that includes user devices 14, one or
more distributed storage and task (DST) processing units 16, and
DST storage sets 350, 352, 354, 356. Each of the DST storage sets
350-356 includes one or more DST execution units 36.
In an example of operation, one or more user devices 14 (e.g.,
video surveillance equipment of a building with multiple cameras)
send streaming data 358 (e.g., video, audio, multimedia, or other
type of data) to a first processing device 355 (e.g., a DST
processing unit 16 and/or one or more processing modules thereof).
For a variety of reasons, the first processing device 355 may evoke
a multi-step dispersed storage error encoding method to error
encode and disperse store the streaming data 358. For example, the
first processing device 355 may evoke the method due to the data
size of the streaming data. As another example, the first
processing device 355 may evoke the method to conserve processing
resources (for other tasks) while receiving the streaming data. As
yet another example, the first processing device 355 may evoke the
method in response to a command.
When the method is evoked, the first processing device 355, via one
or more of its processing modules, performs a first portion of a
dispersed storage error encoding function on the streaming data 358
to produce a plurality of sets of a threshold number of encoded
data slices. For example, the processing module(s) segments the
streaming data into data segments. For a data segment, the
processing module(s) performs a first portion of the dispersed
storage error encoding function on the segment to produce a set of
a threshold number of encoded data slices. As an example of the
first portion of the dispersed storage error encoding function, the
processing module(s) arranges the data segment into a data matrix,
selects a portion of encoding matrix, and creates a partial coded
matrix from the data matrix and the partial encoding matrix. The
processing module(s) arranges the partial coded matrix into a set
of the threshold number of encoded data slices.
As a specific example, assume that a form of Reed Solomon encoding
is used as the dispersed storage error encoding function, where,
for a data segment, five encoded data slices are created and any
three of them are needed to reconstruct the data segment.
Accordingly, an encoding matrix includes five rows of three
coefficients and the data segment is arranged into a data matrix
having three rows of "n" number of data words. While "n" could be
any positive integer, assume "n" is 4 for this example. The partial
encoding matrix includes any three rows of the encoding matrix. For
example, the partial encoding matrix may include the first three
rows, which may correspond to a unity matrix. The processing
module(s) multiplies the data matrix by the partial encoding matrix
to produce the partial coded matrix, which includes three rows of
four encoded values. The processing module(s) then arranges the
encoded values of the partial coded matrix into the set of a
threshold number of encoded data slices. While this example
utilized a form of Reed Solomon encoding, other types of encoding
may be used, including, but not limited to, an information
dispersal algorithm, on-line codes, forward error correction,
erasure codes, convolution encoding, Trellis encoding, Golay,
Multidimensional parity, Hamming, Bose Ray Chauduri Hocquenghem
(BCH), and/or Cauchy-Reed-Solomon. For these other examples of
encoding the first portion corresponds to a level of encoding to
produce enough encoded values to recapture the data segment and the
second portion corresponds to a level of encoding to produce a
desired number of encoded values for error correction of the data
segment.
As the processing module(s) of the first processing device 355 is
creating sets of the threshold number of encoded data slices, it is
alternatingly sending them to a first memory 350 of the DSN (e.g.,
memory of a first set of DST units) and a second memory 354 of the
DSN (e.g., memory of a second set of DST units). The alternating
may be done on a set-by-set basis, a group of sets by group of sets
basis, or based on time (e.g., for a given period of time, send
sets to one of the memories and then for the next interval of time,
send sets to the other one of the memories). While the processing
module(s) is sending one or more sets to the first or the second
memory, it places that memory in a write only mode. As is known,
when a hard drive is processing only write commands without
interruption for read commands, the hard drive functions more
efficiently. The efficiency increases when a multitude of hard
drives are being written to in this manner, which is the case in
this example since each DST unit 36 of the first or second memory
includes at least ten hard drives.
When the first and second memories 350 and 354 are not receiving
one or more sets of the threshold number of encoded data slices,
they are taken out of the write only mode. The first or second
memory may be taken out of the write only mode by placing it in a
read only mode or by removing the write only mode and not
specifying another mode.
After at least some of the sets of the threshold number of encoded
data slices are stored in the first and second memories (e.g.,
milliseconds, seconds, hours, days, weeks), a second processing
device (e.g., other processing module(s) of the first DST
processing unit 16 or another DST processing unit 16) reads sets of
the threshold number of encoded data slices from the first memory
when the first memory is not in the write only mode. After reading
the sets, the second processing device performs a second portion of
the dispersed storage error encoding function on the read sets of
the threshold number of encoded data slices to produce sets of
redundancy encoded data slices. For example, a processing module(s)
of the second process devices performs the second portion of the
dispersed storage error encoding function on a set of the threshold
number of encoded data slices to produce a set of redundancy
encoded data slices, wherein the set of threshold number of encoded
data slices and the set of redundancy encoded data slices
collectively provides a set of encoded data slices.
As an example of the second portion of the dispersed storage error
encoding function, the processing module(s) decode the set of
threshold number of encoded data slices to recapture the data
segment. The processing module(s) then arrange the recaptured data
segment into a data matrix, selects a second portion of encoding
matrix, and creates a second partial coded matrix from the data
matrix and the second partial encoding matrix. The processing
module(s) arranges the second partial coded matrix into the set of
redundancy encoded data slices.
As a specific example, assume that a form of Reed Solomon encoding
is used as the dispersed storage error encoding function, where,
for a data segment, five encoded data slices are created and any
three of them are needed to reconstruct the data segment.
Accordingly, an encoding matrix includes five rows of three
coefficients and the data segment is arranged into a data matrix
having three rows of "n" number of data words. While "n" could be
any positive integer, assume "n" is 4 for this example. The second
partial encoding matrix includes any two rows of the encoding
matrix. For example, the second partial encoding matrix may include
the last two rows, where the first three rows may correspond to a
unity matrix. The processing module(s) multiplies the data matrix
by the second partial encoding matrix to produce the second partial
coded matrix, which includes two rows of four encoded values. The
processing module(s) then arranges the encoded values of the second
partial coded matrix into the set of redundancy encoded data
slices.
After the second processing device has created the sets of
redundancy encoded data slices, it stores them in a third memory
352 of the DSN (e.g., memory of a third set of DST units 36). Note
that the second processing device may place the third memory 352 in
a write only mode before storing the redundancy encoded data slices
therein.
A third processing device (e.g., another DST processing unit 16 or
other processing modules of one or more of the other DST processing
units 16) performs a similar function on the sets of the threshold
number of encoded data slices that are stored in the second memory.
In particular, when the second memory is not in the write only
mode, the third processing module reads and then decodes the set of
the threshold number of encoded data slices to recapture data
segments. For each recaptured data segment, the third processing
device performs the second portion of the dispersed storage error
encoding function to produce a set of redundancy encoded data
slices, which it stores in a fourth memory 356 of the DSN (e.g., a
fourth set of DST units 36).
When the streaming data has ended, the sets of redundancy encoded
data slices may be transferred from the third memory to the first
memory to produce first sets of encoded data slices. Similarly, the
sets of redundancy encoded data slices may be transferred from the
fourth memory to the second memory to produce second sets of
encoded data slices. The first sets of encoded data slices may be
further transferred to the second memory such that a plurality of
sets of encoded data slices for the streaming data are stored in
the second memory. Transferring of the sets of redundancy encoded
data slices, the first and/or second set of encoded data slices,
and/or the sets of the threshold number of encoded data slices may
be done in a variety of ways between the four memories. Regardless
of the encoded data slices are transferred, an address mapping is
created to track where the sets of encoded data slices of the
streaming data are stored.
FIG. 40B is a schematic block diagram of an embodiment of a
dispersed storage system that includes a computing device 370, a
first processing device 372, a second processing device 374, and a
dispersed storage network (DSN) 376. The DSN 376 includes a
plurality of memories including a first memory 378, a second memory
380, a third memory 382, and a fourth memory 384. The computing
device 370 includes a module 388 and may be a user device, a DST
processing unit 16, or other device within the system. Each of the
first and second processing devices 372 and 374 includes a module
390 and 391 and may be a DST processing unit 16, one or more
processing modules of a DST execution unit 16, and/or other device
in the system. Each of the memories 378-384 includes a plurality of
memory devices 386 (e.g., a set of DST units 36, each of which
includes a plurality of disk drives, or the like).
In an example of operation, the computing device 370 receives a
stream of data (or streaming data) 394. Via the module 388, the
computing device 370 alternatingly sends a first portion of the
stream of data 394-1 to the first processing device 372 and a
second portion of the stream of data 394-2 to the second processing
device 374. The computing device 370 may alternate the sending of
the streaming data in accordance with alternating first and second
time intervals (which may be of the same duration, different
durations, and/or varying durations). Accordingly, the computing
device 370 sends the streaming data to the first processing device
during the first time intervals and sends the streaming data to the
second processing device during the second time intervals.
The first processing device 372, via module 390, performs the first
portion of the dispersed storage error encoding function on the
first alternating portions of the streaming data to produce first
sets of the threshold number of encoded data slices. When the first
memory 378 is in the write only mode, the first processing device
372 writes the first sets of the threshold number of encoded data
slices 396 to the first memory 378. Similarly, the second
processing device performs the first portion of the dispersed
storage error encoding function on the second alternating portion
of the streaming data 394-2 to produce second sets of the threshold
number of encoded data slices 400. When the third memory 382 is in
the write only mode, the second processing device 374 writes the
second sets of the threshold number of encoded data slices to the
third memory 382.
When the first memory 378 is not in the write only mode, the first
processing device 372 reads the first sets of the threshold number
of encoded data slices 396 from the first memory 378. The first
processing device 372 then decodes the first sets of the threshold
number of encoded data slices to produce a first set of
reconstructed data segments. For each reconstructed data segment,
the first processing device performs a second portion of the
dispersed storage error encoding function to produce a set of
redundancy encoded data slices 398. The first processing device
writes the sets of redundancy encoded data slices 398 to the second
memory 380.
When the third memory 382 is not in the write only mode, the second
processing device 374 reads the second sets of the threshold number
of encoded data slices 400 from the third memory 382. The second
processing device 374 then decodes the second sets of the threshold
number of encoded data slices to produce a second set of
reconstructed data segments. For each reconstructed data segment,
the second processing device performs a second portion of the
dispersed storage error encoding function to produce a set of
redundancy encoded data slices 402. The second processing device
writes the sets of redundancy encoded data slices 402 to the fourth
memory 384.
When the streaming data has ended, the sets of redundancy encoded
data slices may be transferred from the second memory to the first
memory to produce first sets of encoded data slices. Similarly, the
sets of redundancy encoded data slices may be transferred from the
fourth memory to the third memory to produce second sets of encoded
data slices. The first sets of encoded data slices may be further
transferred to the third memory such that a plurality of sets of
encoded data slices for the streaming data are stored in the third
memory. Transferring of the sets of redundancy encoded data slices,
the first and/or second set of encoded data slices, and/or the sets
of the threshold number of encoded data slices may be done in a
variety of ways between the four memories. Regardless of the
encoded data slices are transferred, an address mapping is created
to track where the sets of encoded data slices of the streaming
data are stored.
FIG. 40C is a flowchart illustrating an example of storing data.
The method begins at step 410 where a processing module of a
computing device alternatingly sends a stream of data to a first
processing device or to a second processing device, where each of
the first and second processing devices is in a write-processing
mode or in a read-processing mode. The alternatingly sending the
stream of data includes a series of sending steps. A first sending
step includes establishing an alternating first time interval and
second time interval. A second sending step includes sending the
stream of data to the first processing device during the first time
interval. A third sending step includes sending the stream of data
to the second processing device during the second time interval.
The first and second time intervals may be the same duration,
different durations, fixed for the stream of data, and/or varying
for the stream of data. The processing module may further
alternatingly send the stream of data to the first processing
device, to the second processing device, or to a third processing
device, where each of the first, second, and third processing
devices is in the write-processing mode, in the read-processing
mode, or is in a wait mode (e.g., idle).
The method continues at step 412 where the first processing device
establishes the write-processing mode when the first processing
device is receiving the stream of data. The establishing includes
setting the first memory in a write only mode when the first
processing device is in the write-processing mode. The setting
includes at least one of selecting a first set of memory devices as
the first memory, sending a write mode of operation request to the
first memory, and suspending read requests from transmission to the
first memory.
When in the write-processing mode, the method continues at step 414
where the first processing device performs a first portion of a
dispersed storage error encoding function on the received stream of
data to produce a plurality of sets of a threshold number of
encoded data slices. The first portion of the dispersed storage
error encoding function corresponding to a level of encoding to
produce the plurality of sets of the threshold number of encoded
data slices.
The method continues at step 416 where the first processing device
writes the sets of the threshold number of encoded data slices into
a first memory of a dispersed storage network (DSN). For example,
the processing module issues at least a threshold number of write
slice requests to a threshold number of storage devices of the
first memory, where the threshold number of write slice requests
includes the plurality of sets of the threshold number of encoded
data slices.
The method continues at step 418 where the first processing device
establishes the read-processing mode when the first processing
device is not receiving the stream of data. The first processing
device establishes this mode by setting the first memory in a read
only mode, which includes at least one of: sending a read mode of
operation request to the first memory and suspending write requests
from transmission to the first memory.
When in the read-processing mode, the method continues at step 420
where the first processing device reads the sets of the threshold
number of encoded data slices from the first memory. The method
continues at step 422 where the first processing device performs a
second portion of the dispersed storage error encoding function
using the sets of the threshold number of encoded data slices to
produce sets of redundancy encoded data slices. The second portion
of the dispersed storage error encoding function corresponds to a
level of encoding to produce the sets of the redundancy encoded
data slices.
The method continues at step 424 where the first processing device
writes the sets of redundancy encoded data slices into a second
memory of the DSN. The method continues at step 426 where the
processing module of the computing device and/or of the first
and/or second processing devices generates an address mapping of
the stream of data to the first and second memories, where the
address mapping links a set of the threshold number of encoded data
slices with a corresponding set of redundancy encoded data slices
to produce a set of encoded data slices.
While the method shows that steps 428-440 are done subsequently to
step 426, these steps may actually be done in parallel with steps
412-424. At step 428, the second processing module establishes the
write-processing mode when the second processing device is
receiving the stream of data. The method continues at step 430
where the second processing device performs the first portion of
the dispersed storage error encoding function on the received
stream of data to produce sets of a threshold number of encoded
data slices. The method continues at step 432 where the second
processing device writes the sets of the threshold number of
encoded data slices into a third memory of the DSN.
The method continues at step 434 where the second processing device
establishes the read-processing mode when the second processing
device is not receiving the stream of data. When in the
read-processing mode, the method continues at step 436 where the
second processing device reads the sets of the threshold number of
encoded data slices from the third memory. The method continues at
step 438 where the second processing device performs the second
portion of the dispersed storage error encoding function using the
sets of the threshold number of encoded data slices to produce a
set of redundancy encoded data slices. The method continues at step
440 where the second processing device writes the sets of
redundancy encoded data slices into fourth memory of the DSN.
Alternatively, or in addition to, the second processing device
writes the second plurality of sets of redundancy encoded data
slices into the second memory of the DSN.
FIG. 41A is a schematic block diagram of another embodiment of a
distributed computing system that includes a user device 14, a DST
client module 34 (which may be included in a DST processing unit
16, a user device, and/or one or more DST EX units 36), and a DST
storage set 442. The DST storage set 442 includes a plurality of
DST execution units 36 that are arranged into encoded data storage
devices and redundancy encoded data storage devices. For example,
the encoded data storage devices includes a decode threshold number
of DST execution units 36 (i.e., the DST EX units in this group
storage a decode threshold number of encoded data slices of an
encoded data segment to recapture the data segment) and the
redundancy encoded data storage devices includes DST execution
units 36 that store remaining encoded data slices of a set of
encoded data slices of the encoded data segment. As a specific
example, data segments of the streaming data 444 are encoded into
sets of five encoded data slices, where, for a data segment, three
of the encoded data slices are stored in the encoded data slice
storage group of devices and the remaining two encoded data slices
are stored in the redundancy encoded data slice storage group of
devices.
Prior to receiving the streaming data 444, the set of DST ET units
(e.g., a set of storage devices) performs a method to establish
which of the DST EX units 36 will be in the group of encoded data
slice storage devices 452 and which will be in the group of
redundancy encoded data slice storage devices 454. The method will
be described in greater detail with reference to FIG. 41C.
In an example of operation after the DST EX units 36 are configured
into the groups, the user device sends streaming data 444 (e.g.,
streaming video, audio, text, graphics, multimedia, etc.) to the
DST client module 34. The DST client module 34 divides the
streaming data 444 into data segments and partially encodes each of
the data segments in accordance with dispersed storage error
encoding parameters to produce, for a data segment, a decode
threshold number of encoded data slices 1-3. For example, the DST
client module 34 performs a first portion of the dispersed storage
error encoding function to produce the decode threshold number of
encoded data slices.
For each encoded data segment, the DST client module 34 sends the
decode threshold number of encoded data slices to DST execution
units 36 within the group of encoded data slice storage devices.
For example of storing encoded data slices of an encoded data
segment, encoded data slice 1 may be stored by a first DST EX unit
36, encoded data slice 2 may be stored by a second DST EX unit 36,
and encoded data slice 3 may be stored by a third DST EX unit
36.
Having stored encoded data slices for an encoded data segment, each
of the DST execution unit 36 of the group of encoded data slice
storage devices sends information 446 regarding its stored encoded
data slice to the DST EX units in the group of redundancy encoded
data slice storage devices. For example, the information 446 may be
the stored encoded data slices themselves such that the DST
execution units 36 in the group of redundancy encoded data slice
storage devices creates redundancy encoded data slices (e.g., the
remaining encoded data slices of a set of encoded data slices for a
data segment) and stores them. In another example, the information
446 may be partially encoded data slices, which the DST execution
unit 36 decodes to produce the redundancy encoded data slices. An
example of creating and decoding partially encoded data slices will
be discussed with reference to FIG. 41B.
FIG. 41B is a schematic block diagram of another embodiment of a
dispersed storage system that includes a set of storage devices
450, where each storage device 456 includes a selection module 458,
an encoding module 460, a redundancy module 462, and memory 464.
The set of storage devices 450 self configures into encoded data
storage devices 452 and redundancy encoded data storage devices 454
by executing the method of FIG. 41C. The storage devices 456 may be
DST EX unit 36, where storage devices 456-1 of the encoded data
slice storage devices 452 utilize the selection module 458, the
encode module 460, and the memory 464, while storage devices 456-2
of the redundancy encoded data slice storage devices 454 utilize
the selection module 458, the redundancy module 462, and memory
464.
In an example of self-configuring, the set of storage devices
coordinates to select dispersed storage error encoding parameters
for storing a stream of data. For example, the set of storage
devices coordinate determining, via the selection module(s) 458, an
error encoding method (e.g., Reed Solomon, an information dispersal
algorithm, on-line codes, forward error correction, erasure codes,
convolution encoding, Trellis encoding, Golay, Multidimensional
parity, Hamming, Bose Ray Chauduri Hocquenghem (BCH), and/or
Cauchy-Reed-Solomon, etc.). The set also determines the number of
coded words, or encoded slices, to create for a given data segment
(e.g., pillar width) and the number code words, or encoded slices,
needed to recover the data segment (e.g., a decode threshold). The
set 450 may further determine how the stream of data is to be
segmented into data segments (e.g., fixed size, varying size,
etc.). Still further, the set 450 may determine whether the data
segments are to be encrypted, compresses, integrity information
created therefor, etc. prior to encoding (e.g., pre-error encoding
data processing). The set 450 may even further determine whether
the encoded data slices are to be encrypted, compressed, integrity
information created therefor, etc. As a specific example, the set
of storage devices determines that, for each data segment,
integrity information is to be created prior to encoding, five code
word or encoded data slices are to be created from the encoding,
and three of them are needed to recover the data segment.
The set of storage devices 450 coordinates, via the selection
module(s) 458, dividing the set of storage devices into the encoded
data storage devices 452 and the redundancy encoded data storage
devices 454. For example and based on the selected dispersed
storage error encoding parameters, the set 450 selects a number of
storage units for encoded data storage devices 452 to correspond to
the selected decode threshold and a number of storage units for the
redundancy encoded data storage devices to correspond to the number
of encoded slices minus the decode threshold.
In an example of processing a stream of data 394 and with the set
of storage devices 450 divided into the two sub-sets 452 and 454,
the storage devices of the encoded data storage devices 452
coordinate storage of a decode threshold amount of encoded data of
the stream of data. For example, an encoding module 460 of one of
the storage devices in sub set 452 divides the stream of data 394
into data segments and encodes, on a data segment by data segment
basis, a data segment into a decode threshold number of encoded
data slices. As a particular example, the encoding module 460
performs a first portion of a dispersed storage error encoding
function. For an encoded data segment, the encoding module 460
sends the decode threshold number of encoded data slices to the
memories 464 of the storage devices in the sub-set 452. For
example, if the encoding module 460 creates three encoded data
slices for an encoded data segment, it sends one of the encoded
data slices to its memory 464, sends another encoded data slice to
the memory 464 of another storage device 456-1, and sends the third
encoded data slice to the memory 464 of a third storage device
456-1. Alternatively, the encoding may be done in a distribute
manner between the encoding modules 460 of the storage devices
460.
Having stored, or while storing, the decode threshold amount of
encoded data, the encoded data storage devices 452 create
information regarding the decode threshold amount of encoded data
468. For example and on a data segment by data segment basis, the
encoded data storage devices 452 create information regarding the
decode threshold number of encoded data slices. The information may
be the encoded data slices, partially encoded data slices, and/or
other information that may be used to create the remaining encoded
data slices of a set of encoded data slices for a data segment
(e.g., redundancy encoded data slices).
As a specific example and on a data segment by data segment basis,
an encoding module 460 of the encoded data storage devices 452
creates partially encoded data slices for a data segment by
obtaining an encoding matrix and reducing it to produce a square
matrix that includes rows associated with the decode threshold
number encoded data slices. The encoding module 460 then inverts
the square matrix to produce an inverted matrix. The encoding
module 460 then matrix multiplies the inverted matrix by a
corresponding encoded data slice 466 to produce a data vector
(e.g., a partially decoded data segment). The encoding module 460
then matrix multiplies the data vector by a row of the encoding
matrix corresponding to an encoded data slice of the decode
threshold number of encoded data slices to produce a partial
encoded redundancy slice. This process is repeated for each of the
redundancy encoded data slice to be created. The encoded data
storage devices 452 then send the information regarding the decode
threshold amount of encoded data 468 to the redundancy encoded data
storage devices 454.
The redundancy encoded data storage devices 454 generate redundancy
encoded data based on the information regarding the decode
threshold amount of encoded data 468 and in accordance with the
dispersed storage error encoding parameters. For example and on a
data segment by data segment basis, one or more of the redundancy
encoded data storage devices 454 receive information regarding the
decode threshold number of encoded data slices. The storage
device(s) 456-2 processes the information regarding the decode
threshold number of encoded data slices to produce the remaining
encoded data slices of the set of encoded data slices for a data
segment (e.g., the redundancy encoded data slices). As a specific
example, the storage device(s) 456-2 performs a second portion of a
dispersed storage error encoding function.
As another specific example, a redundancy module 462 of the storage
device(s) 456-2 process the partially encoded data slices by
summing the partially error coded data in a field such as modulo
some prime. For instance, the redundancy module 462 receives a
decode threshold number of partial encoded redundancy slices and
performs an exclusive OR function on the partial encoded redundancy
slices to produce one or more redundancy encoded data slices 470.
The redundancy encoded data storage devices 454 stores the
redundancy encoded data. For example, the storage devices 454
stores the redundancy encoded data slices for a data segment.
Note that the coordinating done by the set of storage devices, by
the encoded data storage devices, and/or by the redundancy encoded
data storage devices may be done in a centralized manner and/or in
a distribute manner. Further, from coordinating step to
coordinating step (e.g., selection of dispersed storage error
encoding parameters, selection of grouping the storage devices,
storing a decoded threshold amount of encoded data, etc.), the
manner may change from centralized to distributed, or vice
versa.
FIG. 41C is a flowchart illustrating another example of storing
data. The method begins at step 480 where a set of storage devices
coordinates selection of dispersed storage error encoding
parameters for storing a stream of data. The storage devices select
the dispersed storage error encoding parameters by determining one
or more of a redundancy factor, an encoding pillar width, a decode
threshold, a data segmenting process, pre-error encoding data
processing, and post-error encoding data processing.
The method continues at step 482 where the set of storage devices
coordinates selection of which storage devices to include in a
group of encoded data storage devices and which storage devices to
include in a group of redundancy encoded data storage devices. For
example, the set coordinates dividing the storage devices into the
sub-sets by determining, based on the dispersed storage error
encoding parameters, a data segment threshold number (e.g.,
determining the decode threshold for a data segment) and a
redundancy factor (e.g., for a data segment, the number of encoded
data slices in a set of encoded data slices minus the decode
threshold number of encoded data slices). The set then selects
storage devices to be in the group of encoded data storage devices
based on the data segment threshold number and selects storage
devices to be in the group of redundancy encoded data storage
devices based on the redundancy factor. As a specific example, if
the data segment threshold number is three and the redundancy
factor is two, then the set selects three storage devices for
inclusion in the group of encoded data storage devices and two
storage devices for inclusion in the group of redundancy encoded
data storage devices.
The method continues at step 484 where the encoded data storage
devices coordinate storage of a decode threshold amount of encoded
data (e.g., a decode threshold number of encoded data slices for a
data segment of the stream of data), in accordance with the
dispersed storage error encoding parameters. For example, the
encoded data storage devices coordinate partitioning the stream of
data into a stream of data partitions, or data segments, and
coordinating encoding the data segments into set of the decode
threshold number of encoded data slices.
The method continues at step 486 where the encoded data storage
devices send information regarding the decode threshold amount of
encoded data to the redundancy encoded data storage devices. For
example, the encoded data storage devices send a corresponding
portion (e.g., an encoded data slice) of the decode threshold
amount of encoded data. As another example, the encoded data
storage devices generate partially error coded data (e.g., a
partial encoded redundancy slice) based on a corresponding portion
of the decode threshold amount of encoded data (e.g., an encoded
data slice) and send the partially error coded data to the
redundancy encoded data storage devices.
The method continues at step 488 where the redundancy encoded data
storage devices generate redundancy encoded data (e.g., redundancy
encoded data slices) based on the information regarding the decode
threshold amount of encoded data and in accordance with the
dispersed storage error encoding parameters. For example, a
redundancy encoded data storage device receives corresponding
portions of the decode threshold amount of encoded data (e.g., the
decode threshold number of encoded data slices for a data segment)
and generates a corresponding portion of the redundancy encoded
data therefrom. As another example, a redundancy encoded data
storage device receives partially error coded data and generates a
corresponding portion of the redundancy encoded data therefrom
(e.g., summing the partial encoded redundancy slices in a field
such as modulo some prime). The method continues at step 490 where
the redundancy encoded data storage devices store the redundancy
encoded data to provide error encoded reliable storage of the
stream of data.
FIG. 42 is a flowchart illustrating another example of storing
data. The method begins at step 492 where a processing module
(e.g., of a distributed storage and task (DST) client module of a
DST execution unit) receives a portion of a data stream. The method
continues at step 494 where the processing module stores the
portion of the data stream. The method continues at step 496 where
the processing module determines a number of error coded slices per
set of encoded data slices. The method continues at step 498,
where, for each error coded slice, the processing module encodes
the portion of the data stream to produce a partial encoded data
slice. The method continues at step 500 where the processing module
caches the partial encoded data slice. The method continues at step
502 where the processing module identifies a DST execution unit
corresponding to the error coded slice. The identifying includes at
least one of a lookup, receiving an identifier, and identifying the
DST execution unit corresponding to the error coded slice when a
pillar identifier associated with the DST extension unit compares
favorably (e.g., substantially the same) to a pillar identifier of
the error coded slice.
The method continues at step 504 where the processing module
determines a communication capability level associated with the DST
execution unit corresponding to the error coded slice. The
communication capability level includes one or more of a network
bandwidth, a latency, and an activity level. The determining may be
based on one or more of a query, a test, an error message, and a
lookup. When the communication capability level compares favorably
to a communication threshold, the method continues at step 506
where the processing module outputs the partial encoded data slice
to the corresponding DST execution unit.
FIG. 43A is a schematic block diagram of another embodiment of a
distributed computing system that includes an internet server 508
and a content delivery network (CDN) 510. The CDN 510 includes a
front-line cache memory 512, a distributed storage and task (DST)
client module 34, and a distributed storage and task network (DSTN)
module 22. The DSTN module 22 includes a plurality of DST execution
units 36 or storage devices. Alternatively, any number of internet
servers 508 may be operably coupled to the CDN 510. Alternatively,
the DST client module 34 may be implemented in the internet server
508.
The internet server 508 is operable to receive a data access
request 514 (e.g., via the internet) from a requesting entity,
present the data access request 514 to the CDN 510, receive a data
access response 518 from the CDN 510, and present the data access
response 518 to the requesting entity. The data access request 514
includes one or more of an access type indicator, a requesting
entity identifier, and data 516 for storage. For example, the data
access request 514 includes a store data request access type
indicator and the data 516 for storage when the data access request
514 is in regards to storing new data. As another example, the data
access request 514 includes a retrieve data request access type
indicator when the data access request 514 is in regards to
retrieving the data 516. The data access response 518 includes one
or more of a response type indicator, the requesting entity
identifier, and retrieved data of data 516.
The DST client module 34 receives data 516 from a store data access
request and stores the data 516 in the frontline cache memory 512.
Subsequent to storing the data 516 in the frontline cache memory
512 (e.g., 10 minutes later), the DST client module 34 determines
whether the data 516 stored in the frontline cache memory 512
substantially matches data stored in the DSTN module 22. The
determining may be based on one or more of comparing the data 516
to the data stored in the DSTN module 22, comparing a deterministic
value calculated from the data 516 to a deterministic value
calculated from the data stored in the DSTN module, a lookup, and
receiving an indication. When the DST client module 34 determines
that the data 516 stored in the frontline cache memory 512 does not
substantially match data stored in the DSTN module, the DST client
module 34 facilitate storing the data 516 in the DSTN module 22.
The facilitating includes retrieving the data 516 from the
frontline cache memory 512, encoding the data 516 utilizing a
dispersed storage error coding function to produce a plurality of
sets of encoded data slices, and sending the plurality of sets of
encoded data slices to the DSTN module 22 for storage therein.
Subsequent to storing the data in the DSTN module 22, the DST
client module 34 may delete the data 516 from the frontline cache
memory 512. The deleting includes determining when to delete 516.
The determining when to delete includes at least one of determining
that a time period has expired since storing the data 516 in the
DSTN module 22, receiving a delete request, and determining that
available memory space of the frontline cache memory 512 is less
than a memory low threshold level.
Data 516 may be retrieved from the CDN when the data access request
514 includes a retrieve data request. The DST client module 34
receives a data access request 514 that includes a retrieve data
request type. The DST client module 34 determines a storage
location associated with the data 516. The storage location
includes at least one of a storage address (e.g., a memory device
identifier, an offset within the memory device) of the frontline
cache memory 512 and a storage address (e.g., a DSTN address, a
source name, a plurality of sets of slice names) of the DSTN module
22. The determining includes at least one of a lookup, receiving
storage location information, and a query. When the DST client
module 34 determines that the data five and 16 is stored in the
frontline cache memory 512, the DST client module 34 retrieves the
data 516 from the frontline cache memory 512. When the DST client
module 34 determines that the data 516 is not stored in the
frontline cache memory 512, the DST client module retrieves the
data 516 from the DSTN module 22. Retrieving the data 516 from the
DSTN module 22 includes generating a plurality of sets of read
slice requests, sending the plurality of sets of read slice
requests to the DSTN module 22, receiving at least a decode
threshold number of encoded data slices for each set of the
plurality of sets of encoded data slices, and decoding the least
the decode threshold number of encoded data slices for each set of
the plurality of sets of encoded data slices utilizing the
dispersed storage error coding function to reproduce the data 516.
Next, the DST client module 34 generates a data access response 518
that includes the data 516 and outputs the data access response 518
to the internet server 508 for delivery to a requesting entity.
FIG. 43B is a flowchart illustrating another example of storing
data. The method begins at step 520 where a processing module
(e.g., of a distributed storage and task (DST) client module)
receives data for storage. The receiving the data may include
receiving a data access request that includes a store data access
type and the data. The method continues at step 522 where the
processing module stores the data in cache memory. The storing may
include identifying a storage address and updating a storage
location table to include a data identifier of the data in the
storage address.
The method continues at step 524 where the processing module
determines whether data stored in the cache memory is substantially
the same as data stored in a dispersed storage and task network
(DSTN) module. The method branches to step 530 when the processing
module determines that the data stored in the cache memory is not
identical to data stored in the DSTN module. The method continues
to step 526 when the processing module determines that the data
stored in the cache memory is substantially the same as data stored
in the DSTN module.
The method continues at step 526 where the processing module
determines whether to facilitate deletion of the data from the
cache memory when the data stored in the cache memory is
substantially the same as the data stored in the DSTN module. The
determining may be based on one or more of a time period expiring
since storage of the data in the DSTN module, determining that a
data access frequency level is less than an access threshold,
receiving a request, and a schedule. The method continues at step
528 where the processing module facilitates deletion of the data
from the cache memory when deleting the data. The facilitating
includes at least one of erasing the data from the cache memory,
overwriting the data with random data, updating a storage location
table to indicate that the data is disassociated with the cache
memory, and generating a delete signal to the cache memory for the
data. The method continues at step 530 where the processing module
facilitates storage of the data in the DSTN module when the data
stored in the cache memory is not identical to the data stored in
the DSTN module (e.g., retrieve data, encode the data to produce
slices, send the slices to the DSTN module for storage
therein).
FIG. 44A is a schematic block diagram of another embodiment of a
distributed computing system that includes a distributed storage
and task (DST) storage set 532. The DST storage set 532 includes a
set of DST execution units 36. The set of DST execution units 36
includes a decode threshold number of DST execution units 36
corresponding to a decode threshold number of data streams 1-3 and
other DST execution units 36 corresponding to error coded data
slices associated with the decode threshold number of data streams
1-3. The other DST execution units 36 includes a difference of a
pillar width number and a decode threshold number of DST execution
units 36. For example, the decode threshold number of DST execution
units 36 includes three DST execution units 36 and the other DST
execution units includes two DST execution units 36 when a decode
threshold number is three and a pillar width number is five.
The decode threshold number of DST execution units 36 receive a
decode threshold number of data streams 1-3 and stores data slices
of the data streams 1-3. A first DST execution unit 36 of the
decode threshold number of DST execution units 36 receives data
stream 1, encodes data stream 1 to produce one or more slices
associated with a first pillar, generates one or more slice names
corresponding to the one more slices of the first pillar, and
stores the one or more first pillar slices and the corresponding
one more first pillar slice names (e.g., in a local memory of the
first DST execution unit 36). The generating a first slice name of
the one or more first pillar slice names includes generating a
source name corresponding to a first set of slices that includes a
first slice associated with the first slice name. A second DST
execution unit 36 of the decode threshold number of DST execution
units 36 receives data stream 2, encodes data stream 2 to produce
one or more slices associated with a second pillar, generates one
or more slice names corresponding to the one more slices of the
second pillar, and stores the one or more second pillar slices and
the corresponding one more second pillar slice names (e.g., in a
local memory of the second DST execution unit 36). The generating
of a first slice name of the one or more second pillar slice names
includes obtaining the source name corresponding to the first set
of slices that includes a first slice associated with the first
slice name. As such, each DST execution unit 36 of the decode
threshold number of DST execution units 36 utilizes a common source
name for corresponding slices (e.g., ingested within a similar time
period).
The generating of the source name includes generating a common
source name based on at least one of a common time reference, a
common group data stream identifier, and a predetermined common
reference. For example, a source name is changed every 10 seconds
to be substantially the same as a timestamp at the beginning of
each 10 second interval. The generating of the one or more first
pillar slice names includes generating a slice index associated
with the first DST execution unit 36 (e.g., a pillar number) and
generating a contiguously incrementing segment number entry for
each segment number field of each of the one or more first pillar
slice names. The generating of the one or more first pillar slice
names further includes updating a directory to associate a data
stream identifier and the one or more first pillar slice names.
Such a directory structure is discussed in greater detail of
reference to FIG. 44B.
Each DST execution unit 36 of the decode threshold number of DST
execution units 36 generates a partial encoded data slice 534 for
each of the one or more data slices for each of the other DST
execution units 36. The generating includes generating a slice name
for each partial encoded data slice corresponding to an associated
error coded slice to be stored in the other DST execution units 36.
The generating of a slice name of a partial encoded data slice
includes utilizing the common source name and the pillar index
associated with another corresponding DST execution unit 36. Each
DST execution unit 36 of the decode threshold number of DST
execution units 36 sends a corresponding partial encoded data slice
for each of the one or more data slices for each of the other DST
execution units 36 to each of the other DST execution units 36 such
that each of the other DST execution units 36 may combine a decode
threshold number of partial encoded data slices 534 to produce a
corresponding error coded slice for storage therein.
FIG. 44B is a diagram illustrating an example of a directory 536
that includes a plurality of directory entries. An entry of the
plurality of directory entries includes a data stream identifier
(ID) entry of a data stream identifier field 538, a source name
entry of a source name field 540, and a slice name range entry of a
slice name range field 542. The data stream ID entry identifies a
data stream for ingestion. The source name entry includes a source
name associated with the data stream entry. The slice name range
entry includes a slice name range associated with the data stream
ID entry. Slice names within a slice name range share a common
pillar number and include contiguously incrementing data segment
identifiers. For example, a decode threshold number of data streams
1-3 are associated with a common source name of 1FF during a first
time period, a slice name range of 340-440 is associated with data
slices of data stream 1, a slice name range of 1340-1440 is
associated with data slices of data stream 2, and a slice name
range of 2340-2440 is associated with data slices of data stream
3.
FIG. 44C is a flowchart illustrating another example of storing
data, which include similar steps to FIG. 42. The method begins at
step 544 where a processing module (e.g., of a distributed storage
and task (DST) client module) receives a data stream. The method
continues at step 546 where the processing module stores a portion
of the data stream. For example, the processing module partitions
the data stream to generate a first data slice as a first portion
in accordance with a slice generation approach. The method
continues at step 548 where the processing module determines a
source name. The determining may be based on one or more of
receiving, retrieving, and generating based on at least one of a
timestamp, a list, and a deterministic function performed on a
decode threshold number of data stream identifiers. For example,
the processing module performs an exclusive OR (XOR) function on
data stream identifiers 1-3 to produce the source name. As another
example, the processing module utilizes a current timestamp that
includes date, hour, and minutes as the source name. The processing
module may change the source name from time to time as the data
stream is ingested.
The method continues at step 550 where the processing module
determines a slice name corresponding to the portion of the data
stream and in accordance with the source name. For example, the
processing module identifies a pillar identifier associated with
the data stream to generate a slice index of the slice name. As
another example, the processing module generates a segment
identifier associated with a portion of a plurality of portions
associated with the same data stream. For instance, the processing
module generates a segment ID of 1 for a first portion of the
plurality of portions associated with the same data stream and
generates a segment ID of 2 for a second portion of the plurality
of portions associated with the same data stream etc.
The method continues at step 552 where the processing module
updates a directory to associate a data stream identifier, the
source name, and the slice name. For example, the processing module
generates a new entry to add to the directory that includes the
data stream identifier, the source name, and a slice name range
that includes the slice name when the slice name is a first slice
name of the slice name range. As another example, the processing
module modifies an existing entry of the directory to include a
modified slice name range entry that includes a previous slice name
range and the slice name. The method continues with the steps of
FIG. 42 where the processing module determines a number of error
coded slices per set of encoded data slices and encodes the portion
of the data stream to produce a partial encoded data slice for each
error coded slice. The method continues at step 554 where the
processing module outputs the partial encoded data slice to a
corresponding DST execution unit.
FIG. 45A is a schematic block diagram of another embodiment of a
distributed computing system that includes a data interface module
556, a data transmission medium 564, a cache memory interface 558,
a cache memory 560, a distributed storage and task network (DSTN)
interface 562, a distributed storage and task (DST) client module
34, and a DSTN module 22. The DSTN module 22 includes a plurality
of DST execution units 36. The data transmission medium 564
includes at least one of a waveguide, an optical coupler, a
streaming data signals conductive wire, free space, and a closed
tube signal guide.
The system functions to receive a streaming data message 566 and
simultaneously store data 570 of the streaming data message 566 in
the cache memory 560 and as a plurality of sets of encoded data
slices 572 in the DSTN module 22. The streaming data message 566
may include one or more of data from a high-speed data link, a
multimedia stream, an audio stream, a video stream, and a plurality
of data streams. The data interface module 556 receives the
streaming data message 566 and generates streaming data signals 568
based on the streaming data message 566. The streaming data signals
568 includes at least one of a wireless radio frequency
transmission (e.g., 60 GHz), an optical frequency transmission
(e.g., laser), and a multiplex of at least one of a plurality of
wireless radio frequency transmissions and a plurality of optical
frequency transmissions. The data interface module 556 is discussed
in greater detail with reference to FIG. 45B.
The data interface module 556 outputs the streaming data signals
568 as a one-to-many transmission via the data transmission medium
564 to the cache memory interface 558 and the DSTN interface 562.
The cache memory interface 560 receives the streaming data signals
568 and outputs the data 570 to the cache memory 560 for storage
therein. The outputting includes controlling the cache memory 560
(e.g., activation of a write control). The cache memory interface
558 is discussed in greater detail with reference to FIG. 45C.
The DSTN interface 562 receives the streaming data signals 568 and
outputs the data 570 to the DST client module 34. The outputting
includes generating a storage request to facilitate storage of the
data 570 in the DSTN module 22. The DSTN interface 562 is discussed
in greater detail with reference to FIG. 45D. The DST client module
34 receives the data 570, encodes the data 570 utilizing a
dispersed storage error coding function to produce the plurality of
sets of encoded data slices 572, generates a plurality of sets of
write slice requests that includes the plurality of sets of encoded
data slices 572, and sends the plurality of sets of write slice
requests to the DSTN module 22.
FIG. 45B is a schematic block diagram of an embodiment of a data
interface module 556 that includes a data translator 574 and a data
transmitter 576. The data translator 574 functions to receive a
streaming data message 566 and extract data 578 from the streaming
data message 566. For example, the data translator 574 identifies
non-data elements (e.g., addressing, distribution instructions,
permissions, credentials, addressing information) of the streaming
data message 566 and discards the non-data elements to produce the
data 578. As another example, the data translator 574 identifies
the elements of the streaming data message 566 and extracts the
data elements as the data 578. The data transmitter 576 encodes the
data 578 to produce streaming data signals 568. For example, the
data transmitter 576 modulates a frequency reference with the data
578 to produce a modulated frequency and up-converts the modulated
frequency to a desired frequency (e.g., 60 GHz) of the streaming
data signals 568. The encoding may include appending one or more of
the addressing information, the permissions, the credentials, and
the addressing distribution instructions.
FIG. 45C is a schematic block diagram of an embodiment of a cache
memory interface 558 that includes a data receiver 580 and a memory
controller 582. The data receiver 580 functions to receive
streaming data signals 568 and decode data 584 from the streaming
data signals 568. For example, the data receiver 580 down-converts
the streaming data signals 568 from an operational frequency of the
streaming data signals 568 (e.g., 60 GHz) to an intermediate
frequency and demodulates the intermediate frequency to reproduce
the data 584. The memory controller 582 functions to write at least
some of the data 584 to a cache memory by outputting data 570 as
the data 584 to the cache memory. The outputting includes
activation of at least one control signal to operate the cache
memory. The at least one control signal includes at least one of a
write line and a write request.
FIG. 45D is a schematic block diagram of an embodiment of a
distributed storage and task network (DSTN) interface 562 that
includes a data receiver 580 and a DSTN controller 586. The data
receiver 580 functions to receive streaming data signals 568 and
decode data 588 from the streaming data signals 568. The DSTN
controller 586 functions to generate at least one storage request
that includes the data 588 as data 570 and to output the storage
request to a distributed storage and task (DST) client module to
facilitate storage of the data 570 in a DSTN module.
FIG. 45E is a flowchart illustrating an example of encoding data.
The method begins at step 590 where a processing module (e.g., of a
data interface module) receives a streaming data message. The
method continues at step 592 where the processing module extracts
data from the streaming data message. The extracting includes at
least one of identifying the data and identifying non-data. The
identifying of the data and the non-data may be based on one or
more of addressing information, a lookup, a predetermination, a
streaming data message format, an indicator, and a query. The
method continues at step 594 where the processing module encodes
the data to produce streaming data signals for transmission to a
plurality of memory system interfaces (e.g., modulate an
intermediate frequency with the data, up-convert to an operational
frequency of the streaming data signals). The plurality of memory
system interfaces includes one or more of a cache memory interface
and a distributed storage and task network (DSTN) interface.
FIG. 45F is a flowchart illustrating an example of decoding
streaming data signals. The method begins at step 596 where a
processing module (e.g., of a cache memory interface) receives
streaming data signals. The method continues at step 598 where the
processing module decodes the streaming data signals to reproduce
data (e.g., down-convert and operational fricassee of the streaming
data signals to an intermediate fricassee, demodulate the
intermediate frequency to reproduce the data). The method continues
at step 600 where the processing module generates memory control
signals to write the data to a cache memory. For example, the
processing module activates a write control line to the cache
memory.
FIG. 45G is a flowchart illustrating another example of storing
data, which includes similar steps to FIG. 45F. The method begins
with steps 596 and 598 of FIG. 45F where a processing module (e.g.,
of a distributed storage and task network (DSTN) interface)
receives streaming data signals and decodes the streaming data
signals to reproduce data. The method continues at step 602 where
the processing module generates one or more DSTN storage requests
to facilitate storage of the data in a DSTN module. A DSTN storage
request of the one or more DSTN storage requests includes at least
a portion of the data.
FIG. 46A is a schematic block diagram of another embodiment of a
distributed computing system that includes a distributed storage
and task (DST) processing unit 16 and a distributed storage and
task network (DSTN) module 22. The DST processing unit 16 includes
an interface 30, a DST client module 34, a cache memory 604, and an
interface 32. The cache memory 604 may be implemented utilizing one
or more of a solid-state memory, an optical drive memory, and a
magnetic drive memory. The DSTN module 22 includes a plurality of
DST execution units 36.
The DST processing unit 16 functions to receive data 606 and
facilitate storage of the data 606 in one or more of the cache
memory 604 and in the DSTN module 22 as a plurality of sets of
encoded data slices 608. The DST client module 34 receives the data
606 via the interface 30 and facilitate storage of the data 606 in
the cache memory 604. Subsequent to storage of the data 606 in the
cache memory 604, the DST client module 34 updates a directory to
associate a data identifier of the data 606 with the cache memory
604. Further subsequent to storage of the data 606 in the cache
memory 604, the DST client module 34 retrieves the data 606 from
the cache memory 604, encodes the data 606 to produce a plurality
of sets of encoded data slices 608, generates a plurality of sets
of write slice requests that includes the plurality of sets of
encoded data slices 608, and outputs the plurality of sets of write
slice requests to the DSTN module 22 to facilitate storage of the
data as the plurality of sets of encoded data slices 608 in the
DSTN module 22. Subsequent to storage of the data 606 in the DSTN
module 22, the DST client module 34 facilitates deletion of the
data 606 from the cache memory 604. The deleting includes updating
the directory to indicate a disassociation of the data identifier
of the data 606 with the cache memory 604 and to indicate an
association of the data identifier with the DSTN module 22.
FIG. 46B is a flowchart illustrating another example of storing
data, which includes similar steps to FIG. 43B. The method begins
with steps 520 and 522 of FIG. 43B where a processing module (e.g.,
of a distributed storage and task (DST) client module) receives
data for storage and stores the data in a cache memory. The method
continues at step 610 where the processing module updates a
directory to associate a data identifier (ID) of the data with the
cache memory. The updating includes indicating a storage location
of the cache memory (e.g., device ID, device address, offset) for
the data ID. The method continues at step 612 where the processing
module retrieves the data from the cache memory. The retrieving may
include determining when to retrieve the data from the cache memory
based on one or more of a schedule, a fixed time, when the data was
stored in the cache memory, the data ID, a request, an error
message, a cache memory capacity indicator, and a cache memory
capacity threshold. For example, the processing module determines
to retrieve the data from the cache memory 10 minutes after the
data was stored in the cache memory.
The method continues at step 614 where the processing module
encodes the data to produce a plurality of sets of encoded data
slices utilizing a dispersed storage error coding function. The
method continues at step 616 where the processing module generates
one or more sets of write slice requests that includes the
plurality of sets of encoded data slices. The method continues at
step 618 where the processing module outputs the one or more sets
of write slice requests to a distributed storage and task network
(DSTN) module to facilitate storage of the data in the DSTN module
as slices.
When writing to the DSTN module is confirmed, the method continues
at step 620 where the processing module updates the directory to
associate the data ID with the DSTN module. The processing module
determines that the writing to the DSTN module is confirmed based
on one or more of receiving at least a write threshold number of
commit acknowledgments per set of the plurality of sets of encoded
data slices, receiving a confirmation message, and a query. The
method continues at step 622 where the processing module updates
the directory to disassociate the data ID with the cache memory.
The method continues at step 624 where the processing module
facilitates deletion of the data from the cache memory.
In addition, the processing module may receive a retrieve data
request that includes the data ID. The processing module identifies
a storage location based on a directory lookup utilizing the data
ID. When the storage location indicates that the data is stored in
the cache memory, the processing module retrieves the data from the
cache memory. When a storage location indicates that the data is
not stored in the cache memory, the processing module retrieves the
data from the DSTN module (e.g., generates read slice requests,
receives slices, decodes the slices to reproduce the data).
FIG. 47A is a schematic block diagram of another embodiment of a
distributed computing system that includes a first distributed
storage and task (DST) processing unit 16, a second DST processing
unit 16, and a distributed storage and task network (DSTN) module
22. Alternatively, the system includes more than two DST processing
units 16. The first and second DST processing units 16 each
includes an interface 30, a DST client module 34, a cache memory
604, and an interface 32. The DSTN module 22 includes a plurality
of DST execution units 36.
The DST client module 34 of the first DST processing unit 16
receives data 606 via interface 30 and facilitate storage of the
data 606 in the cache memory 604 associated with the first DST
processing unit 16. The DST client module 34 of the first DST
processing unit 16 updates a directory to associate a data
identifier (ID) of the data 606 with an identifier of the cache
memory 604 of the first DST processing unit 16. The DST client
module 34 of the first DST processing unit 16 identifies the second
DST processing unit 16 as associated with the data ID and sends the
data 606 to the second DST processing unit 16. Alternatively, the
DST client module 34 of the first DST processing unit 16 identifies
a third DST processing unit 16 as associated with the data ID and
sends the data 606 to the third DST processing unit 16. The
identifying includes identifying a DST processing unit 16 that is
associated with the data ID based on one or more of a lookup, a
query, a request, a solicitation, and an error message.
When transfer is confirmed (e.g., the second DST processing unit 16
sends an acknowledgment to the first DST processing unit 16), the
DST client module 34 of the first DST processing unit 16 updates a
directory to associate the data ID with a cache memory identifier
of the second DST processing unit 16. The DST client module 34 of
the first DST processing unit 16 updates the directory to
disassociate the data ID with the ID of the cache memory 604 of the
first DST processing unit 16. The DST client module 34 of the first
DST processing unit 16 facilitates deletion of the data 606 from
the cache memory 604 of the first DST processing unit 16.
The DST client module 34 of the second DST processing unit 16
receives the data 606 and facilitates storage of the data 606 in
the cache memory 604 of the second DST processing unit 16. The DST
client module 34 of the second DST processing unit 16 facilitates
transfer of the data 606 to the DSTN module as slices 608 and
updates the directory to associate the data ID with the DSTN module
22 and to disassociate the data ID with the cache memory ID of the
second DST processing unit 16. The DST client module 34 of the
second DST processing unit 16 facilitates deletion of the data 606
from the cache memory 604 of the second DST processing unit 16.
FIG. 47B is a flowchart illustrating another example of storing
data, which includes similar steps to FIGS. 43B and 46B. The method
begins with steps 520 and 522 of FIG. 43B where a processing module
(e.g., of a distributed storage and task (DST) client module)
receives data for storage and stores the data in cache memory. The
method continues with step 610 of FIG. 46B where the processing
module updates a directory to associate a data identifier (ID) of
the data with the cache memory. The method continues at step 626
where the processing module identifies another DST client module
associated with the data. The identifying may be based on one or
more of a lookup, a query, a request, performing a deterministic
function on the data ID, a random selection, a round-robin
selection, and an error message.
The method continues at step 628 where the processing module
retrieves the data from the cache memory. The method continues at
step 630 where the processing module transfers the data to the
other DST client module. When the transfer is confirmed (e.g., a
time period has expired, a favorable acknowledgment has been
received), the method continues at step 632 where the processing
module updates the directory to associate the data ID with the
other DST client module. The method continues with step 622 and 624
of FIG. 46B where the processing module updates the directory to
disassociate the data ID with the cache memory and to delete the
data from the cache memory.
In addition, the processing module may receive a data retrieval
request that includes the data ID. The processing module identifies
a storage location based on a directory lookup utilizing the data
ID. The processing module retrieves the data from the storage
location and outputs the data to a requesting entity. The retrieval
includes generating read slice requests and decoding slices to
reproduce the data when the data is not stored in the cache memory
or in another cache memory.
FIG. 48 is a flowchart illustrating another example of storing
data, that includes similar steps to FIGS. 43B, 46B, and 47B. The
method begins with step 520 of FIG. 43B where a processing module
(e.g., of a distributed storage and task (DST) client module)
receives data for storage and continues with step 626 and 630 of
FIG. 47B where the processing module identifies another DST client
module associated with the data and transfers the data to the other
DST client module. The method continues at step 634 where the
processing module updates a directory to associate a data
identifier (ID) of the data with the other DST client module.
When a data ingest rate of the other DST client module is less than
a data ingest rate, the method continues at step 636 where the
processing module buffers at least some of the data in a cache
memory. The processing module determines the data ingest rate of
the other DST client module based on at least one of a query, an
error message, a list, a test, and receiving the rate. The
buffering includes identifying how much data buffer such that the
ingest rates balance and the data interest rate of the other DST
client module is greater than the data ingest rate.
When buffering, the method continues at step 638 where the
processing module updates the directory to associate the data ID of
the data with the cache memory. When the data ingest rate of the
other DST client module is greater than the data ingest rate, the
method continues at step 640 where the processing module
facilitates transfer of at least some of the data from the cache
memory to the other DST client module. The facilitating includes
retrieving the data and sending the data to the other DST client
module. When the transfer is confirmed, the method continues with
step 622 of FIG. 46B where the processing module updates the
directory to disassociate the data ID with the cache memory. The
method continues at step 642 where the processing module deletes
the at least some of the data from the cache memory.
As may be used herein, the terms "substantially" and
"approximately" provides an industry-accepted tolerance for its
corresponding term and/or relativity between items. Such an
industry-accepted tolerance ranges from less than one percent to
fifty percent and corresponds to, but is not limited to, component
values, integrated circuit process variations, temperature
variations, rise and fall times, and/or thermal noise. Such
relativity between items ranges from a difference of a few percent
to magnitude differences. As may also be used herein, the term(s)
"operably coupled to", "coupled to", and/or "coupling" includes
direct coupling between items and/or indirect coupling between
items via an intervening item (e.g., an item includes, but is not
limited to, a component, an element, a circuit, and/or a module)
where, for indirect coupling, the intervening item does not modify
the information of a signal but may adjust its current level,
voltage level, and/or power level. As may further be used herein,
inferred coupling (i.e., where one element is coupled to another
element by inference) includes direct and indirect coupling between
two items in the same manner as "coupled to". As may even further
be used herein, the term "operable to" or "operably coupled to"
indicates that an item includes one or more of power connections,
input(s), output(s), etc., to perform, when activated, one or more
of its corresponding functions and may further include inferred
coupling to one or more other items. As may still further be used
herein, the term "associated with", includes direct and/or indirect
coupling of separate items and/or one item being embedded within
another item. As may be used herein, the term "compares favorably",
indicates that a comparison between two or more items, signals,
etc., provides a desired relationship. For example, when the
desired relationship is that signal 1 has a greater magnitude than
signal 2, a favorable comparison may be achieved when the magnitude
of signal 1 is greater than that of signal 2 or when the magnitude
of signal 2 is less than that of signal 1.
As may also be used herein, the terms "processing module",
"processing circuit", and/or "processing unit" may be a single
processing device or a plurality of processing devices. Such a
processing device may be a microprocessor, micro-controller,
digital signal processor, microcomputer, central processing unit,
field programmable gate array, programmable logic device, state
machine, logic circuitry, analog circuitry, digital circuitry,
and/or any device that manipulates signals (analog and/or digital)
based on hard coding of the circuitry and/or operational
instructions. The processing module, module, processing circuit,
and/or processing unit may be, or further include, memory and/or an
integrated memory element, which may be a single memory device, a
plurality of memory devices, and/or embedded circuitry of another
processing module, module, processing circuit, and/or processing
unit. Such a memory device may be a read-only memory, random access
memory, volatile memory, non-volatile memory, static memory,
dynamic memory, flash memory, cache memory, and/or any device that
stores digital information. Note that if the processing module,
module, processing circuit, and/or processing unit includes more
than one processing device, the processing devices may be centrally
located (e.g., directly coupled together via a wired and/or
wireless bus structure) or may be distributedly located (e.g.,
cloud computing via indirect coupling via a local area network
and/or a wide area network). Further note that if the processing
module, module, processing circuit, and/or processing unit
implements one or more of its functions via a state machine, analog
circuitry, digital circuitry, and/or logic circuitry, the memory
and/or memory element storing the corresponding operational
instructions may be embedded within, or external to, the circuitry
comprising the state machine, analog circuitry, digital circuitry,
and/or logic circuitry. Still further note that, the memory element
may store, and the processing module, module, processing circuit,
and/or processing unit executes, hard coded and/or operational
instructions corresponding to at least some of the steps and/or
functions illustrated in one or more of the Figures. Such a memory
device or memory element can be included in an article of
manufacture.
The present invention has been described above with the aid of
method steps illustrating the performance of specified functions
and relationships thereof. The boundaries and sequence of these
functional building blocks and method steps have been arbitrarily
defined herein for convenience of description. Alternate boundaries
and sequences can be defined so long as the specified functions and
relationships are appropriately performed. Any such alternate
boundaries or sequences are thus within the scope and spirit of the
claimed invention. Further, the boundaries of these functional
building blocks have been arbitrarily defined for convenience of
description. Alternate boundaries could be defined as long as the
certain significant functions are appropriately performed.
Similarly, flow diagram blocks may also have been arbitrarily
defined herein to illustrate certain significant functionality. To
the extent used, the flow diagram block boundaries and sequence
could have been defined otherwise and still perform the certain
significant functionality. Such alternate definitions of both
functional building blocks and flow diagram blocks and sequences
are thus within the scope and spirit of the claimed invention. One
of average skill in the art will also recognize that the functional
building blocks, and other illustrative blocks, modules and
components herein, can be implemented as illustrated or by discrete
components, application specific integrated circuits, processors
executing appropriate software and the like or any combination
thereof.
The present invention may have also been described, at least in
part, in terms of one or more embodiments. An embodiment of the
present invention is used herein to illustrate the present
invention, an aspect thereof, a feature thereof, a concept thereof,
and/or an example thereof. A physical embodiment of an apparatus,
an article of manufacture, a machine, and/or of a process that
embodies the present invention may include one or more of the
aspects, features, concepts, examples, etc. described with
reference to one or more of the embodiments discussed herein.
Further, from figure to figure, the embodiments may incorporate the
same or similarly named functions, steps, modules, etc. that may
use the same or different reference numbers and, as such, the
functions, steps, modules, etc. may be the same or similar
functions, steps, modules, etc. or different ones.
While the transistors in the above described figure(s) is/are shown
as field effect transistors (FETs), as one of ordinary skill in the
art will appreciate, the transistors may be implemented using any
type of transistor structure including, but not limited to,
bipolar, metal oxide semiconductor field effect transistors
(MOSFET), N-well transistors, P-well transistors, enhancement mode,
depletion mode, and zero voltage threshold (VT) transistors.
Unless specifically stated to the contra, signals to, from, and/or
between elements in a figure of any of the figures presented herein
may be analog or digital, continuous time or discrete time, and
single-ended or differential. For instance, if a signal path is
shown as a single-ended path, it also represents a differential
signal path. Similarly, if a signal path is shown as a differential
path, it also represents a single-ended signal path. While one or
more particular architectures are described herein, other
architectures can likewise be implemented that use one or more data
buses not expressly shown, direct connectivity between elements,
and/or indirect coupling between other elements as recognized by
one of average skill in the art.
The term "module" is used in the description of the various
embodiments of the present invention. A module includes a
processing module, a functional block, hardware, and/or software
stored on memory for performing one or more functions as may be
described herein. Note that, if the module is implemented via
hardware, the hardware may operate independently and/or in
conjunction software and/or firmware. As used herein, a module may
contain one or more sub-modules, each of which may be one or more
modules.
While particular combinations of various functions and features of
the present invention have been expressly described herein, other
combinations of these features and functions are likewise possible.
The present invention is not limited by the particular examples
disclosed herein and expressly incorporates these other
combinations.
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